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ACM Doctoral Dissertation Award

About ACM Doctoral Dissertation Award

Presented annually to the author(s) of the best doctoral dissertation(s) in computer science and engineering. The Doctoral Dissertation Award is accompanied by a prize of $20,000, and the Honorable Mention Award is accompanied by a prize totaling $10,000. Winning dissertations will be published in the ACM Digital Library as part of the ACM Books Series.

Recent Doctoral Dissertation Award News

2022 acm doctoral dissertation award.

Aayush Jain is the recipient of the 2022 ACM Doctoral Dissertation Award for his dissertation “ Indistinguishability Obfuscation From Well-Studied Assumptions ,” which established the feasibility of mathematically rigorous software obfuscation from well-studied hardness conjectures.

The central goal of software obfuscation is to transform source code to make it unintelligible without altering what it computes. Additional conditions may be added, such as requiring the transformed code to perform similarly, or even indistinguishably, from the original. As a software security mechanism, it is essential that software obfuscation have a firm mathematical foundation.

The mathematical object that Jain’s thesis constructs, indistinguishability obfuscation, is considered a theoretical “master tool” in the context of cryptography—not only in helping achieve long-desired cryptographic goals such as functional encryption, but also in expanding the scope of the field of cryptography itself. For example, indistinguishability obfuscation aids in goals related to software security that were previously entirely in the domain of software engineering.

Jain’s dissertation was awarded the Best Paper Award at the ACM Symposium on Theory of Computing (STOC 2021) and was the subject of an article in Quanta Magazine titled “Scientists Achieve Crown Jewel of Cryptography.”

Jain is an Assistant Professor at Carnegie Mellon University. He is interested in theoretical and applied cryptography and its connections with related areas of theoretical computer science. Jain received a BTech in Electrical Engineering, and an MTech in Information and Communication Technology from the Indian Institute of Technology, Delhi. He received a PhD in Computer Science from the University of California, Los Angeles.

Honorable Mentions

Honorable Mentions for the 2022 ACM Doctoral Dissertation Award go to Alane Suhr whose PhD was earned at Cornell University, and Conrad Watt , who earned his PhD at the University of Cambridge.

Suhr’s dissertation, “ Reasoning and Learning in Interactive Natural Language Systems ,” was recognized for formulating and designing algorithms for continual language learning in collaborative interactions, and designing methods to reason about context-dependent language meaning. Suhr’s dissertation made transformative contributions in several areas of Natural Language Processing (NLP).

Suhr is an Assistant Professor at the University of California, Berkeley. Suhr’s research is focused on natural language processing, machine learning, and computer vision. Suhr received a BS in Computer Science and Engineering from Ohio State University, as well as a PhD in Computer Science from Cornell University.

Watt’s dissertation, “ Mechanising and Evolving the Formal Semantics of WebAssembly: the Web’s New Low-Level Language ,” establishes a mechanized semantics for WebAssembly and defines its concurrency model. The model will underpin current and future web engineering. His dissertation is considered a stand-out example of developing and using fully rigorous mechanized semantics to directly affect and improve the designs of major pieces of our industrial computational infrastructure.

Watt is a Research Fellow (postdoctoral) at the University of Cambridge, where he focuses on mechanized formal verification, concurrency, and the WebAssembly language. He received a MEng in Computer Science from Imperial College London and a PhD in Computer Science from the University of Cambridge.

Aayush Jain is the recipient of the 2022 ACM Doctoral Dissertation Award for his dissertation “ Indistinguishability Obfuscation From Well-Studied Assumptions .” Honorable Mentions for the 2022 ACM Doctoral Dissertation Award go to Alane Suhr whose PhD was earned at Cornell University, and Conrad Watt , who earned his PhD at the University of Cambridge.

Jain's dissertation established the feasibility of mathematically rigorous software obfuscation from well-studied hardness conjectures.The central goal of software obfuscation is to transform source code to make it unintelligible without altering what it computes. Additional conditions may be added, such as requiring the transformed code to perform similarly, or even indistinguishably, from the original. As a software security mechanism, it is essential that software obfuscation have a firm mathematical foundation.

2022 ACM Doctoral Dissertation Award Honorable Mention

Watt’s dissertation, “ Mechanising and Evolving the Formal Semantics of WebAssembly: The Web’s New Low-Level Language ,” establishes a mechanized semantics for WebAssembly and defines its concurrency model. The model will underpin current and future web engineering. His dissertation is considered a stand-out example of developing and using fully rigorous mechanized semantics to directly affect and improve the designs of major pieces of our industrial computational infrastructure.

2021 ACM Doctoral Dissertation Award

Manish Raghavan is the recipient of the 2021 ACM Doctoral Dissertation Award for his dissertation " The Societal Impacts of Algorithmic Decision-Making ." Raghavan’s dissertation makes significant contributions to the understanding of algorithmic decision making and its societal implications, including foundational results on issues of algorithmic bias and fairness.

Algorithmic fairness is an area within AI that has generated a great deal of public and media interest. Despite being at a very early stage of his career, Raghavan has been one of the leading figures shaping the direction and focus of this line of research.

Raghavan is a Postdoctoral Fellow at the Harvard Center for Research on Computation and Society. His primary interests lie in the application of computational techniques to domains of social concern, including algorithmic fairness and behavioral economics, with a particular focus on the use of algorithmic tools in the hiring pipeline. Raghavan received a BS degree in Electrical Engineering and Computer Science from the University of California, Berkeley, and MS and PhD degrees in Computer Science from Cornell University.

Honorable Mentions for the 2021 ACM Doctoral Dissertation Award go to Dimitris Tsipras of Stanford University, Pratul Srinivasan of Google Research and Benjamin Mildenhall of Google Research.

Dimitris Tsipras’ dissertation, “ Learning Through the Lens of Robustness ,” was recognized for foundational contributions to the study of adversarially robust machine learning (ML) and building effective tools for training reliable machine learning models. Tsipras made several pathbreaking contributions to one of the biggest challenges in ML today: making ML truly ready for real-world deployment.

Tsipras is a Postdoctoral Scholar at Stanford University. His research is focused on understanding and improving the reliability of machine learning systems when faced with the real world. Tsipras received a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, as well as SM and PhD degrees in computer science from the Massachusetts Institute of Technology (MIT).

Pratul Srinivasan and Benjamin Mildenhall are awarded Honorable Mentions for their co-invention of the Neural Radiance Field (NeRF) representation, associated algorithms and theory, and their successful application to the view synthesis problem. Srinivasan’s dissertation, " Scene Representations for View Synthesis with Deep Learning ," and Mildenhall’s dissertation, “ Neural Scene Representations for View Synthesis ,” addressed a long-standing open problem in computer vision and computer graphics. That problem, called “view synthesis” in vision and “unstructured light field rendering” in graphics, involves taking just a handful of photographs of a scene and predicting new images from any intermediate viewpoint. NeRF has already inspired a remarkable volume of follow-on research, and the associated publications have received some of the fastest rates of citation in computer graphics literature—hundreds in the first year of post-publication.

Srinivasan is a Research Scientist at Google Research, where he focuses on problems at the intersection of computer vision, computer graphics, and machine learning. He received a BSE degree in Biomedical Engineering and BA in Computer Science from Duke University and a PhD in Computer Science from the University of California, Berkeley.

Mildenhall is a Research Scientist at Google Research, where he works on problems in computer vision and graphics. He received a BS degree in Computer Science and Mathematics from Stanford University and a PhD in Computer Science from the University of California, Berkeley.

2020 ACM Doctoral Dissertation Award

Chuchu Fan is the recipient of the 2020 ACM Doctoral Dissertation Award for her dissertation, “ Formal Methods for Safe Autonomy: Data-Driven Verification, Synthesis, and Applications .” The dissertation makes foundational contributions to verification of embedded and cyber-physical systems, and demonstrates applicability of the developed verification technologies in industrial-scale systems.

Fan’s dissertation also advances the theory for sensitivity analysis and symbolic reachability; develops verification algorithms and software tools (DryVR, Realsyn); and demonstrates applications in industrial-scale autonomous systems.

Key contributions of her dissertation include the first data-driven algorithms for bounded verification of nonlinear hybrid systems using sensitivity analysis. A groundbreaking demonstration of this work on an industrial-scale problem showed that verification can scale. Her sensitivity analysis technique was patented, and a startup based at the University of Illinois at Urbana-Champaign has been formed to commercialize this approach.

Fan also developed the first verification algorithm for “black box” systems with incomplete models combining probably approximately correct (PAC) learning with simulation relations and fixed point analyses. DryVR, a tool that resulted from this work, has been applied to dozens of systems, including advanced driver assist systems, neural network-based controllers, distributed robotics, and medical devices.

Additionally, Fan’s algorithms for synthesizing controllers for nonlinear vehicle model systems have been demonstrated to be broadly applicable. The RealSyn approach presented in the dissertation outperforms existing tools and is paving the way for new real-time motion planning algorithms for autonomous vehicles.

Fan is the Wilson Assistant Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology, where she leads the Reliable Autonomous Systems Lab. Her group uses rigorous mathematics including formal methods, machine learning, and control theory for the design, analysis, and verification of safe autonomous systems. Fan received a BA in Automation from Tsinghua University. She earned her PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign.

Honorable Mentions for the 2020 ACM Doctoral Dissertation Award go to Henry Corrigan-Gibbs and Ralf Jung .

Corrigan-Gibbs’s dissertation, “ Protecting Privacy by Splitting Trust ,” improved user privacy on the internet using techniques that combine theory and practice. Corrigan-Gibbs first develops a new type of probabilistically checkable proof (PCP), and then applies this technique to develop the Prio system, an elegant and scalable system that addresses a real industry need. Prio is being deployed at several large companies, including Mozilla, where it has been shipping in the nightly version of the Firefox browser since late 2019, the largest-ever deployment of PCPs.

Corrigan-Gibbs’s dissertation studies how to robustly compute aggregate statistics about a user population without learning anything else about the users. For example, his dissertation introduces a tool enabling Mozilla to measure how many Firefox users encountered a particular web tracker without learning which users encountered that tracker or why. The thesis develops a new system of probabilistically checkable proofs that lets every browser send a short zero-knowledge proof that its encrypted contribution to the aggregate statistics is well formed. The key innovation is that verifying the proof is extremely fast.

Corrigan-Gibbs is an Assistant Professor in the Electrical Engineering and Computer Science Department at the Massachusetts Institute of Technology, where he is also a member of the Computer Science and Artificial Intelligence Lab. His research focuses on computer security, cryptography, and computer systems. Corrigan-Gibbs received his PhD in Computer Science from Stanford University.

Ralf Jung’s dissertation, “ Understanding and Evolving the Rust Programming Language ,” established the first formal foundations for safe systems programming in the innovative programming language Rust. In development at Mozilla since 2010, and increasingly popular throughout the industry, Rust addresses a longstanding problem in language design: how to balance safety and control. Like C++, Rust gives programmers low-level control over system resources. Unlike C++, Rust also employs a strong “ownership-based” system to statically ensure safety, so that security vulnerabilities like memory access errors and data races cannot occur. Prior to Jung’s work, however, there had been no rigorous investigation of whether Rust’s safety claims actually hold, and due to the extensive use of “unsafe escape hatches” in Rust libraries, these claims were difficult to assess.

In his dissertation, Jung tackles this challenge by developing semantic foundations for Rust that account directly for the interplay between safe and unsafe code. Building upon these foundations, Jung provides a proof of safety for a significant subset of Rust. Moreover, the proof is formalized within the automated proof assistant Coq and therefore its correctness is guaranteed. In addition, Jung provides a platform for formally verifying powerful type-based optimizations, even in the presence of unsafe code.

Through Jung's leadership and active engagement with the Rust Unsafe Code Guidelines working group, his work has already had profound impact on the design of Rust and laid essential foundations for its future.

Jung is a post-doctoral researcher at the Max Planck Institute for Software Systems and a research affiliate of the Parallel and Distributed Operating Systems Group at the Massachusetts Institute of Technology. His research interests include programming languages, verification, semantics, and type systems. He conducted his doctoral research at the Max Planck Institute for Software Systems, and received his PhD, Master's, and Bachelor's degrees in Computer Science from Saarland University.

Chuchu Fan is the recipient of the 2020 ACM Doctoral Dissertation Award for her dissertation, “ Formal Methods for Safe Autonomy: Data-Driven Verification, Synthesis, and Applications .” Honorable Mentions go to Henry Corrigan-Gibbs of the Massachusetts Institute of Technology and Ralf Jung of the Max Planck Institute for Software Systems and MIT.

Fan’s dissertation makes foundational contributions to verification of embedded and cyber-physical systems, and demonstrates applicability of the developed verification technologies in industrial-scale systems. Her dissertation also advances the theory for sensitivity analysis and symbolic reachability; develops verification algorithms and software tools (DryVR, Realsyn); and demonstrates applications in industrial-scale autonomous systems.

2020 ACM Doctoral Dissertation Award Honorable Mention

2019 acm doctoral dissertation award.

Dor Minzer of Tel Aviv University is the recipient of the 2019 ACM Doctoral Dissertation Award for his dissertation, “ On Monotonicity Testing and the 2-to-2-Games Conjecture .” Honorable Mentions go to Jakub Tarnawski of École polytechnique fédérale de Lausanne (EPFL) and JiaJun Wu of Massachusetts Institute of Technology.

Dor Minzer's dissertation, “ On Monotonicity Testing and the 2-to-2-Games Conjecture ,” settles the complexity of testing monotonicity of Boolean functions and makes a significant advance toward resolving the Unique Games Conjecture, one of the most central problems in approximation algorithms and complexity theory.

Property-testers are extremely efficient randomized algorithms that check whether an object satisfies a certain property, when the data is too large to examine. For example, one may want to check that the distance between any two computers in the internet network does not exceed a given bound. In the first part of his thesis, Minzer settled a famous open problem in the field by introducing an optimal tester that checks whether a given Boolean function (voting scheme) is monotonic.

The holy grail of complexity theory is to classify computational problems to those that are feasible and those that are infeasible. The PCP theorem (for probabilistically checkable proofs) establishes the framework that enables classifying approximation problems as infeasible, showing they are NP-hard. In 2002, Subhash Khot proposed the Unique Games Conjecture (UGC), asserting that a very strong version of the PCP theorem should still hold. The conjecture has inspired a flurry of research and has had far-reaching implications. If proven true, the conjecture would explain the complexity of a whole family of algorithmic problems. In contrast to other conjectures, UGC has been controversial, splitting the community into believers and skeptics. While progress toward validating the conjecture has stalled, evidence against it had been piling up, involving new algorithmic techniques.

In the second part of his dissertation, Minzer went halfway toward establishing the conjecture, and in the process nullified the strongest known evidence against UGC. Even if UGC is not resolved in the immediate future, Minzer’s dissertation makes significant advances toward solving research problems that have previously appeared out of reach.

Minzer is a postdoctoral researcher at the Institute for Advanced Study (IAS) in Princeton, New Jersey, and will be joining MIT as an Assistant Professor in the fall of 2020. His main research interests are in computational complexity theory, PCP, and analysis of Boolean functions. Minzer received a BA in Mathematics, as well as an MSc and PhD in Computer Science from Tel Aviv University.

Dor Minzer of Tel Aviv University is the recipient of the 2019 ACM Doctoral Dissertation Award for his dissertation, “ On Monotonicity Testing and the 2-to-2-Games Conjecture .” The key contributions of Minzer’s dissertation are settling the complexity of testing monotonicity of Boolean functions and making a significant advance toward resolving the Unique Games Conjecture, one of the most central problems in approximation algorithms and complexity theory.

Honorable Mentions for the 2019 ACM Doctoral Dissertation Award go to Jakub Tarnawski , École polytechnique fédérale de Lausanne (EPFL) and JiaJun Wu , Massachusetts Institute of Technology (MIT).

Jakub Tarnawski’s dissertation “ New Graph Algorithms via Polyhedral Techniques ” made groundbreaking algorithmic progress on two of the most central problems in combinatorial optimization: the matching problem and the traveling salesman problem. Work on deterministic parallel algorithms for the matching problem is motivated by one of the unsolved mysteries in computer science: does randomness help in speeding up algorithms? Tarnawski’s dissertation makes significant progress on this question by almost completely derandomizing a three-decade-old randomized parallel matching algorithm by Ketan Mulmuley, Umesh Vaziriani, and Vijay Vazirani.

The second major result of Tarnawski’s dissertation relates to the traveling salesman problem: find the shortest tour of n given cities. Already in 1956, George Dantzig et al. used a linear program to solve a special instance of the problem. Since then the strength of their linear program has become one of the main open problems in combinatorial optimization. Tarnawski’s dissertation resolves this question asymptotically and gives the first constant-factor approximation algorithm for the asymmetric traveling salesman problem.

Tarnawski is a researcher at Microsoft Research. He is broadly interested in theoretical computer science and combinatorial optimization, particularly in graph algorithms and approximation algorithms. He received his PhD from EPFL and an MSc in Mathematics and Computer Science from the University of Wrocław, Poland.

JiaJun Wu’s dissertation, “ Learning to See the Physical World ,” has advanced AI for perceiving the physical world by integrating bottom-up recognition in neural networks with top-down simulation engines, graphical models, and probabilistic programs. Despite phenomenal progress in the past decade, current artificial intelligence methods tackle only specific problems, require large amounts of training data, and easily break when generalizing to new tasks or environments. Human intelligence reveals how far we need to go: from a single image, humans can explain what we see, reconstruct the scene in 3D, predict what’s going to happen, and plan our actions accordingly.

Wu addresses the problem of physical scene understanding—how to build efficient and versatile machines that learn to see, reason about, and interact with the physical world. The key insight is to exploit the causal structure of the world, using simulation engines for computer graphics, physics, and language, and to integrate them with deep learning. His dissertation spans perception, physics and reasoning, with the goal of seeing and reasoning about the physical world as humans do. The work bridges the various disciplines of artificial intelligence, addressing key problems in perception, dynamics modeling, and cognitive reasoning.

Wu is an Assistant Professor of Computer Science at Stanford University. His research interests include physical scene understanding, dynamics models, and multi-modal perception. He received his PhD and SM degree in Electrical Engineering and Computer Science from MIT, and Bachelor’s degrees in Computer Science and Economics from Tsinghua University in Beijing, China.

2019 ACM Doctoral Dissertation Award Honorable Mention

2018 acm doctoral dissertation award.

Chelsea Finn of the University of California, Berkeley is the recipient of the 2018 ACM Doctoral Dissertation Award for her dissertation, “ Learning to Learn with Gradients .” In her thesis, Finn introduced algorithms for meta-learning that enable deep networks to solve new tasks from small datasets, and demonstrated how her algorithms can be applied in areas including computer vision, reinforcement learning and robotics.

Deep learning has transformed the artificial intelligence field and has led to significant advances in areas including speech recognition, computer vision and robotics. However, deep learning methods require large datasets, which aren’t readily available in areas such as medical imaging and robotics.

Meta-learning is a recent innovation that holds promise to allow machines to learn with smaller datasets. Meta-learning algorithms “learn to learn” by using past data to learn how to adapt quickly to new tasks. However, much of the initial work in meta-learning focused on designing increasingly complex neural network architectures. In her dissertation, Finn introduced a class of methods called model-agnostic meta-learning (MAML) methods, which don’t require computer scientists to manually design complex architectures. Finn’s MAML methods have had tremendous impact on the field and have been widely adopted in reinforcement learning, computer vision and other fields of machine learning.

At a young age, Finn has become one of the most recognized experts in the field of robotic learning. She has developed some of the most effective methods to teach robots skills to control and manipulate objects. In one instance highlighted in her dissertation, she used her MAML methods to teach a robot reaching and placing skills, using raw camera pixels from just a single human demonstration.

Finn is a Research Scientist at Google Brain and a postdoctoral researcher at the Berkeley AI Research Lab (BAIR). In the fall of 2019, she will start a full-time appointment as an Assistant Professor at Stanford University. Finn received her PhD in Electrical Engineering and Computer Science from the University of California, Berkeley and a BS in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.

Honorable Mentions for the 2018 ACM Doctoral Dissertation Award go to Ryan Beckett and Tengyu Ma , who both received PhD degrees in Computer Science from Princeton University.

Ryan Beckett developed new, general and efficient algorithms for creating and validating network control plane configurations in his dissertation, “ Network Control Plane Synthesis and Verification .” Computer networks connect key components of the world’s critical infrastructure. When such networks are misconfigured, several systems people rely on are interrupted—airplanes are grounded, banks go offline, etc. Beckett’s dissertation describes new principles, algorithms and tools for substantially improving the reliability of modern networks. In the first half of his thesis, Beckett shows that it is unnecessary to simulate the distributed algorithms that traditional routers implement—a process that is simply too costly—and that instead, one can directly verify the stable states to which such algorithms will eventually converge. In the second half of his thesis, he shows how to generate correct configurations from surprisingly compact high-level specifications.

Beckett is a researcher in the mobility and networking group at Microsoft Research. He received his PhD and MA in Computer Science from Princeton University, and both a BS in Computer Science and a BA in Mathematics from the University of Virginia.

Tengyu Ma’s dissertation, " Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding ,” develops novel theory to support new trends in machine learning. He introduces significant advances in proving convergence of nonconvex optimization algorithms in machine learning, and outlines properties of machine learning models trained via such methods. In the first part of his thesis, Ma studies a range of problems, such as matrix completion, sparse coding, simplified neural networks, and learning linear dynamical systems, and formalizes clear and natural conditions under which one can design provable correct and efficient optimization algorithms. In the second part of his thesis, Ma shows how to understand and interpret the properties of embedding models for natural languages, which were learned using nonconvex optimization.

Ma is an Assistant Professor of Computer Science and Statistics at Stanford University. He received a PhD in Computer Science from Princeton University and a BS in Computer Science from Tsinghua University.

2018 ACM Doctoral Dissertation Award Honorable Mention

Chelsea Finn of the University of California, Berkeley is the recipient of the 2018 ACM Doctoral Dissertation Award for her dissertation, “ Learning to Learn with Gradients .” Honorable Mentions go to Ryan Beckett and Tengyu Ma , who both received PhD degrees in Computer Science from Princeton University.

Beckett developed new, general and efficient algorithms for creating and validating network control plane configurations in his dissertation, “ Network Control Plane Synthesis and Verification .” Computer networks connect key components of the world’s critical infrastructure. When such networks are misconfigured, several systems people rely on are interrupted—airplanes are grounded, banks go offline, etc. Beckett’s dissertation describes new principles, algorithms and tools for substantially improving the reliability of modern networks. In the first half of his thesis, Beckett shows that it is unnecessary to simulate the distributed algorithms that traditional routers implement—a process that is simply too costly—and that instead, one can directly verify the stable states to which such algorithms will eventually converge. In the second half of his thesis, he shows how to generate correct configurations from surprisingly compact high-level specifications.

Ma’s dissertation, " Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding ,” develops novel theory to support new trends in machine learning. He introduces significant advances in proving convergence of nonconvex optimization algorithms in machine learning, and outlines properties of machine learning models trained via such methods. In the first part of his thesis, Ma studies a range of problems, such as matrix completion, sparse coding, simplified neural networks, and learning linear dynamical systems, and formalizes clear and natural conditions under which one can design provable correct and efficient optimization algorithms. In the second part of his thesis, Ma shows how to understand and interpret the properties of embedding models for natural languages, which were learned using nonconvex optimization.

2017 ACM Doctoral Dissertation Award

Aviad Rubinstein is the recipient of the Association for Computing Machinery (ACM) 2017 Doctoral Dissertation Award for his dissertation “ Hardness of Approximation Between P and NP .” In his thesis, Rubinstein established the intractability of the approximate Nash equilibrium problem and several other important problems between P and NP-completeness—an enduring problem in theoretical computer science.

For several decades, researchers in areas including economics and game theory have developed mathematical equilibria models to predict how people in a game or economic environment might act given certain conditions.

When applying computational approaches to equilibria models, important questions arise, including how long it would take a computer to calculate an equilibrium. In theoretical computer science, a problem that can be solved in theory (given finite resources, such as time) but for which, in practice, any solution takes too many resources (that is, too much time) to be useful is known as an intractable problem. In 2008, Daskalakis, Goldberg and Papadimitriou demonstrated the intractability of the Nash equilibrium, an often-examined scenario in game theory and economics where no player in the game would take a different action as long as every other player in the game remains the same. But a very large question remained in theoretical computer science as to whether an approximate Nash equilibrium (a variation of the Nash equilibrium that allows the possibility that a player may have a small incentive to do something different) is also intractable.

Rubinstein’s dissertation introduced brilliant new ideas and novel mathematical techniques to demonstrate that the approximate Nash equilibrium is also intractable. Beyond solving this important question, Rubinstein’s thesis also insightfully addressed other problems around P and NP completeness, the most important question in theoretical computer science. Rubinstein is a postdoctoral researcher at Harvard University and will be starting an appointment as an Assistant Professor at Stanford University in the fall of 2018. He received a PhD in Computer Science from the University of California, Berkeley, an MSc in Computer Science from Tel Aviv University (Israel) and a BSc in Mathematics and Computer Science from Technion (Israel).

Honorable Mentions for the 2017 ACM Doctoral Dissertation Award went to Mohsen Ghaffari , who received his PhD from the Massachusetts Institute of Technology’s Department of Electrical Engineering and Computer Science (MIT EECS) and Stefanie Mueller , who received her PhD from the Hasso Plattner Institute (Germany).

In Ghaffari’s dissertation, “ Improved Distributed Algorithms for Fundamental Graph Problems ,” he presents novel distributed algorithms that significantly lower the costs of solving fundamental graph problems in networks, including structuring problems, connectivity problems, and scheduling problems. Ghaffari’s dissertation includes both breakthrough algorithmic contributions and interesting methodology. The first part of the dissertation presents a new maximal independent set (MIS) algorithm, which is a breakthrough because it achieves a better time bound than previous algorithms for this three-decades-old problem. The second part of the dissertation contains a collection of related results about vertex connectivity decompositions. Finally, in the third part of his dissertation, Ghaffari introduces a time-efficient algorithm for concurrent scheduling of multiple distributed algorithms. Ghaffari is an Assistant Professor of Computer Science at ETH Zurich. He received a PhD and SM in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and received a double major in Computer Science and Electrical Engineering from Sharif University (Iran).

Mueller’s dissertation, “ Interacting with Personal Fabrication Devices ,” demonstrates how to make personal fabrication machines interactive. Her approach involves two steps: speeding of batch processing and turn taking, and real-time interaction. Her software systems faBrickator, WirePrint and Platener allow users to fabricate 10 times faster, a process she calls low-fidelity fabrication or low-fab. In her dissertation she also outlines how to add interactivity. Constructable, a tool she developed, allows workers to fabricate by sketching directly on the workpiece, causing a laser cutter to implement these sketches when the user stops drawing. Another of Mueller’s tools, LaserOrigami, extends this work to 3D. Mueller is an Assistant Professor of Computer Science at MIT EECS and MIT CSAIL. She received a PhD in Computer Science as well as an MSc in IT-Systems Engineering from the Hasso Plattner Institute (Germany). Earlier, she received a BSc in Computer Science and Media from the University of Applied Science Harz (Germany).

2017 ACM Doctoral Dissertation Award Honorable Mention

Aviad Rubinstein is the recipient of the Association for Computing Machinery (ACM) 2017 Doctoral Dissertation Award for his dissertation “ Hardness of Approximation Between P and NP .” Honorable Mentions for the award went to Mohsen Ghaffari , who received his PhD from the Massachusetts Institute of Technology’s Department of Electrical Engineering and Computer Science (MIT EECS) and Stefanie Mueller , who received her PhD from the Hasso Plattner Institute (Germany).

2017 ACM Doctoral Dissertation Award Award Honorable Mention

Aviad Rubinstein is the recipient of the Association for Computing Machinery (ACM) 2017 Doctoral Dissertation Award for his dissertation “ Hardness of Approximation Between P and NP .” Honorable Mentions for the award went to Mohsen Ghaffari , who received his PhD from the Massachusetts Institute of Technology’s Department of Electrical Engineering and Computer Science (MIT EECS) and Stefanie Mueller , who received her PhD from the Hasso Plattner Institute (Germany).

2016 ACM Doctoral Dissertation Award

Haitham Hassanieh is the recipient of the ACM 2016 Doctoral Dissertation Award . Hassanieh developed highly efficient algorithms for computing the Sparse Fourier Transform, and demonstrated their applicability in many domains including networks, graphics, medical imaging and biochemistry. In his dissertation, The Sparse Fourier Transform: Theory and Practice , he presented a new way to decrease the amount of computation needed to process data, thus increasing the efficiency of programs in several areas of computing.

In computer science, the Fourier transform is a fundamental tool for processing streams of data. It identifies frequency patterns in the data, a task that has a broad array of applications. For many years, the Fast Fourier Transform (FFT) was considered the most efficient algorithm in this area. With the growth of Big Data, however, the FFT cannot keep up with the massive increase in datasets. In his doctoral dissertation Hassanieh presents the theoretical foundation of the Sparse Fourier Transform (SFT), an algorithm that is more efficient than FFT for data with a limited number of frequencies. He then shows how this new algorithm can be used to build practical systems to solve key problems in six different applications including wireless networks, mobile systems, computer graphics, medical imaging, biochemistry and digital circuits. Hassanieh’s Sparse Fourier Transform can process data at a rate that is 10 to 100 times faster than was possible before, thus greatly increasing the power of networks and devices.

Hassanieh is an Assistant Professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at the University of Illinois at Urbana-Champaign. He received his MS and PhD in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT). A native of Lebanon, he earned a BE in Computer and Communications Engineering from the American University of Beirut. Hassanieh’s Sparse Fourier Transform algorithm was chosen by MIT Technology Review as one of the top 10 breakthrough technologies of 2012. He has also been recognized with the Sprowls Award for Best Dissertation in Computer Science, and the SIGCOMM Best Paper Award.

Honorable Mention for the 2016 ACM Doctoral Dissertation Award went to Peter Bailis of Stanford University and Veselin Raychev of ETH Zurich.

In Bailis’s dissertation, Coordination Avoidance in Distributed Databases , he addresses a perennial problem in a network of multiple computers working together to achieve a common goal: Is it possible to build systems that scale efficiently (process ever-increasing amounts of data) while ensuring that application data remains provably correct and consistent? These concerns are especially timely as Internet services such as Google and Facebook have led to a vast increase in the global distribution of data. In addressing this problem, Bailis introduces a new framework, invariant confluence, that mitigates the fundamental tradeoffs between coordination and consistency. His dissertation breaks new conceptual ground in the areas of transaction processing and distributed consistency—two areas thought to be fully understood. Bailis is an Assistant Professor of Computer Science at Stanford University. He received a PhD in Computer Science from the University of California, Berkeley and his AB in Computer Science from Harvard College.

Raychev’s dissertation, Learning from Large Codebases , introduces new methods for creating programming tools based on probabilistic models of code that can solve tasks beyond the reach of current methods. As the size of publicly available codebases has grown dramatically in recent years, so has interest in developing programming tools that solve software tasks by learning from these codebases. Raychev’s dissertation takes a novel approach to addressing this challenge that combines advanced techniques in programming languages with machine learning practices. In the thesis, Raychev lays out four separate methods that detail how machine learning approaches can be applied to program analysis in order to produce useful programming tools. These include: code completion with statistical language models; predicting program properties from big code; learning program from noisy data; and learning statistical code completion systems. Raychev’s work is regarded as having the potential to open up several promising new avenues of research in the years to come. Raychev is currently a co-founder and Chief Technology Officer of DeepCode, a company developing artificial intelligence-based programming tools. He received a PhD in Computer Science from ETH Zurich. A native of Bulgaria, he received MS and BS degrees from Sofia University.

2016 ACM Doctoral Dissertation Honorable Mention Award

Haitham Hassanieh is the recipient of the ACM 2016 Doctoral Dissertation Award . Honorable Mention for the 2016 ACM Doctoral Dissertation Award went to Peter Bailis of Stanford University and Veselin Raychev of ETH Zurich.

Honorable Mention for the 2016 ACM Doctoral Dissertation Award went to Peter Bailis of Stanford University and Veselin Raychev of ETH Zurich.

Carnegie Mellon Graduate Earns ACM Doctoral Dissertation Award

Julian Shun has won the 2015 ACM Doctoral Dissertation Award presented by ACM for providing evidence that, with appropriate programming techniques, frameworks and algorithms, shared-memory programs can be simple, fast and scalable. In his dissertation Shared-Memory Parallelism Can Be Simple, Fast, and Scalable , he proposes new techniques for writing scalable parallel programs that run efficiently both in theory and in practice.

While parallelism is essential to achieving high performance in computing, writing efficient and scalable programs can be very difficult. Shun’s three-pronged approach to writing parallel programs that he outlines in his thesis includes:

proposing tools and techniques for deterministic parallel programming;
the introduction of Ligra, the first high-level shared-memory framework for parallel graph traversal algorithms; and
presenting new algorithms for a variety of important problems on graphs and strings that are both efficient in theory and practice.

Shun is a post-doctoral researcher at the University of California, Berkeley, where he was awarded a Miller Research Fellowship. He earned his Ph.D. at Carnegie Mellon University, which nominated him for the ACM Doctoral Dissertation Award. He earned a B.A. in Computer Science from the University of California, Berkeley, where he was ranked first in the 2008 graduating class of computer science students. During the 2013-2014 academic year, he was the recipient of a Facebook Graduate Fellowship.

He will receive the Doctoral Dissertation Award and its $20,000 prize at the annual ACM Awards Banquet on June 11 in San Francisco. Financial sponsorship of the award is provided by Google Inc.

Honorable Mention

Honorable mention for the 2015 ACM Doctoral Dissertation Award went to Aaron Sidford of the Massachusetts Institute of Technology, and Siavash Mirarab of the University of Texas at Austin. They will share a $10,000 prize, with financial sponsorship provided by Google Inc.

In Sidford’s dissertation, Iterative Methods, Combinatorial Optimization, and Linear Programming Beyond the Universal Barrier , he considers the fundamental problems in continuous and combinatorial optimization that occur pervasively in practice, and shows how to improve upon the best-known theoretical running times for solving these problems across a broad range of parameters. Sidford uses and improves techniques from diverse disciplines including spectral graph theory, numerical analysis, data structures, and convex optimization to provide the first theoretical improvements in decades for multiple classic problems ranging from linear programming to linear system solving to maximum flow. Sidford is presently a postdoctoral researcher at Microsoft New England. He received a Ph.D. in Computer Science from the Massachusetts Institute of Technology, which nominated him for this award.

Mirarab’s dissertation, Novel Scalable Approaches for Multiple Sequence Alignment and Phylogenomic Reconstruction , addresses the growing need to analyze large-scale biological sequence data efficiently and accurately. To address this challenge, Mirarab introduces several methods: PASTA, a scalable and accurate algorithm that can align data sets up to one million sequences; statistical binning, a novel technique for reducing noise in estimation of evolutionary trees for individual parts of the genome; and ASTRAL, a new summary method that can run on 1,000 species in one day and has outstanding accuracy. These methods were essential in analyzing very large genomic datasets of birds and plants. Mirarab is currently an Assistant Professor of Electrical and Computer Engineering at the University of California, San Diego. He obtained a Ph.D. in Computer Science from the University of Texas at Austin, which nominated him for this award.

Creator Of Advanced Data Processing Architecture Wins 2014 Doctoral Dissertation Award

Matei Zaharia won the 2014 Doctoral Dissertation Award for his innovative solution to tackling the surge in data processing workloads, and accommodating the speed and sophistication of complex multi-stage applications and more interactive ad-hoc queries. His work proposed a new architecture for cluster computing systems, achieving best-in-class performance in a variety of workloads while providing a simple programming model that lets users easily and efficiently combine them.

To address the limited processing capabilities of single machines in an age of growing data volumes and stalling process speeds, Zaharia developed Resilient Distributed Datasets (RDDs). As described in his dissertation “An Architecture for Fast and General Data Processing on Large Clusters,” RDDs are a distributed memory abstraction that lets programmers perform computations on large clusters in a faulttolerant manner. He implements RDDs in the open source Apache Spark system, which matches or exceeds the performance of specialized systems in many application domains, achieving up to speeds 100 times faster for certain applications. It also offers stronger fault tolerance guarantees and allows these workloads to be combined.

Zaharia, an assistant professor at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), completed his dissertation at the University of California, Berkeley, which nominated him. A graduate of the University of Waterloo, where he won a gold medal at the ACM International Collegiate Programming Contest (ICPC) in 2005, he earned a Bachelor of Mathematics (B. Math) degree. He is a co-founder and Chief Technology Officer of Databricks, the company that is commercializing Apache Spark.

He will receive the Doctoral Dissertation Award and its $20,000 prize at the annual ACM Awards Banquet on June 20 in San Francisco, CA. Financial sponsorship of the award is provided by Google Inc.

Honorable Mention for the 2014 ACM Doctoral Dissertation Award went to John Criswell of the University of Rochester, and John C. Duchi of Stanford University. They will share a $10,000 prize, with financial sponsorship provided by Google Inc.

Criswell’s dissertation, “Secure Virtual Architecture: Security for Commodity Software Systems,” describes a compiler-based infrastructure designed to address the challenges of securing systems that use commodity operating systems like UNIX or Linux. This Secure Virtual Architecture (SVA) can protect both operating system and application code through compiler instrumentation techniques. He completed a Ph.D. degree in Computer Science from the University of Illinois at Urbana-Champaign, which nominated him for this award.

Duchi’s dissertation, “Multiple Optimality Guarantees in Statistical Learning,” explores tradeoffs that occur in modern statistical and machine learning applications. The criteria for these tradeoffs – computation, communication, privacy – must be optimized to maintain statistical performance. He explores examples from optimization, and shows some of the practical benefits that a focus on multiple optimality criteria can bring about. A graduate of the University of California, Berkeley with an M.A. degree in Statistics and a Ph.D. degree in Computer Science, he was also an undergraduate and masters student at Stanford University. He was nominated by UC Berkeley for this award.

ACM will present these and other awards at the ACM Awards Banquet on June 20, 2015 in San Francisco, CA.

Press Release

Doctoral Dissertation Award Recognizes Young Researchers

Aayush Jain is the recipient of the 2022 ACM Doctoral Dissertation Award for establishing the feasibility of mathematically rigorous software obfuscation from well-studied hardness conjectures. Honorable Mentions for the 2022 ACM Doctoral Dissertation Award go to Alane Suhr whose PhD was earned at Cornell University, and Conrad Watt , who earned his PhD at the University of Cambridge.

View the full list of ACM Awards

Acm awards by category, career-long contributions, early-to-mid-career contributions, specific types of contributions, student contributions, regional awards, how awards are proposed.

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Home > FACULTIES > Computer Science > CSD-ETD

Computer Science Theses and Dissertations

This collection contains theses and dissertations from the Department of Computer Science, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2024 2024

A Target-Based and A Targetless Extrinsic Calibration Methods for Thermal Camera and 3D LiDAR , Farhad Dalirani

Investigating Tree- and Graph-based Neural Networks for Natural Language Processing Applications , Sudipta Singha Roy

Theses/Dissertations from 2023 2023

Classification of DDoS Attack with Machine Learning Architectures and Exploratory Analysis , Amreen Anbar

Multi-view Contrastive Learning for Unsupervised Domain Adaptation in Brain-Computer Interfaces , Sepehr Asgarian

Improved Protein Sequence Alignments Using Deep Learning , Seyed Sepehr Ashrafzadeh

INVESTIGATING IMPROVEMENTS TO MESH INDEXING , Anurag Bhattacharjee

Algorithms and Software for Oligonucleotide Design , Qin Dong

Framework for Assessing Information System Security Posture Risks , Syed Waqas Hamdani

De novo sequencing of multiple tandem mass spectra of peptide containing SILAC labeling , Fang Han

Local Model Agnostic XAI Methodologies Applied to Breast Cancer Malignancy Predictions , Heather Hartley

A Quantitative Analysis Between Software Quality Posture and Bug-fixing Commit , Rongji He

A Novel Method for Assessment of Batch Effect on single cell RNA sequencing data , Behnam Jabbarizadeh

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs , Taabish Jeshani

Citation Polarity Identification From Scientific Articles Using Deep Learning Methods , Souvik Kundu

Denoising-Based Domain Adaptation Network for EEG Source Imaging , Runze Li

Decoy-Target Database Strategy and False Discovery Rate Analysis for Glycan Identification , Xiaoou Li

DpNovo: A DEEP LEARNING MODEL COMBINED WITH DYNAMIC PROGRAMMING FOR DE NOVO PEPTIDE SEQUENCING , Yizhou Li

Developing A Smart Home Surveillance System Using Autonomous Drones , Chongju Mai

Look-Ahead Selective Plasticity for Continual Learning , Rouzbeh Meshkinnejad

The Two Visual Processing Streams Through The Lens Of Deep Neural Networks , Aidasadat Mirebrahimi Tafreshi

Source-free Domain Adaptation for Sleep Stage Classification , Yasmin Niknam

Data Heterogeneity and Its Implications for Fairness , Ghazaleh Noroozi

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System for Efficient, Sustainable, and Self-Adaptive Urban Environments , Elham Okhovat

Evaluating the Likelihood of Bug Inducing Commits Using Metrics Trend Analysis , Parul Parul

On Computing Optimal Repairs for Conditional Independence , Alireza Pirhadi

Open-Set Source-Free Domain Adaptation in Fundus Images Analysis , Masoud Pourreza

Migration in Edge Computing , Arshin Rezazadeh

A Modified Hopfield Network for the K-Median Problem , Cody Rossiter

Predicting Network Failures with AI Techniques , Chandrika Saha

Toward Building an Intelligent and Secure Network: An Internet Traffic Forecasting Perspective , Sajal Saha

An Exploration of Visual Analytic Techniques for XAI: Applications in Clinical Decision Support , Mozhgan Salimiparsa

Attention-based Multi-Source-Free Domain Adaptation for EEG Emotion Recognition , Amir Hesam Salimnia

Global Cyber Attack Forecast using AI Techniques , Nusrat Kabir Samia

IMPLEMENTATION OF A PRE-ASSESSMENT MODULE TO IMPROVE THE INITIAL PLAYER EXPERIENCE USING PREVIOUS GAMING INFORMATION , Rafael David Segistan Canizales

A Computational Framework For Identifying Relevant Cell Types And Specific Regulatory Mechanisms In Schizophrenia Using Data Integration Methods , Kayvan Shabani

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network , Sareh Soltani Nejad

Smartphone Loss Prevention System Using BLE and GPS Technology , Noshin Tasnim

A Hybrid Continual Machine Learning Model for Efficient Hierarchical Classification of Domain-Specific Text in The Presence of Class Overlap (Case Study: IT Support Tickets) , Yasmen M. Wahba

Reducing Negative Transfer of Random Data in Source-Free Unsupervised Domain Adaptation , Anthony Wong

Deep Neural Methods for True/Pseudo- Invasion Classification in Colorectal Polyp Whole-Slide Images , Zhiyuan Yang

Developing a Relay-based Autonomous Drone Delivery System , Muhammad Zakar

Learning Mortality Risk for COVID-19 Using Machine Learning and Statistical Methods , Shaoshi Zhang

Machine Learning Techniques for Improved Functional Brain Parcellation , Da Zhi

Theses/Dissertations from 2022 2022

The Design and Implementation of a High-Performance Polynomial System Solver , Alexander Brandt

Defining Service Level Agreements in Serverless Computing , Mohamed Elsakhawy

Algorithms for Regular Chains of Dimension One , Juan P. Gonzalez Trochez

Towards a Novel and Intelligent e-commerce Framework for Smart-Shopping Applications , Susmitha Hanumanthu

Multi-Device Data Analysis for Fault Localization in Electrical Distribution Grids , Jacob D L Hunte

Towards Parking Lot Occupancy Assessment Using Aerial Imagery and Computer Vision , John Jewell

Potential of Vision Transformers for Advanced Driver-Assistance Systems: An Evaluative Approach , Andrew Katoch

Psychological Understanding of Textual journals using Natural Language Processing approaches , Amirmohammad Kazemeinizadeh

Driver Behavior Analysis Based on Real On-Road Driving Data in the Design of Advanced Driving Assistance Systems , Nima Khairdoost

Solving Challenges in Deep Unsupervised Methods for Anomaly Detection , Vahid Reza Khazaie

Developing an Efficient Real-Time Terrestrial Infrastructure Inspection System Using Autonomous Drones and Deep Learning , Marlin Manka

Predictive Modelling For Topic Handling Of Natural Language Dialogue With Virtual Agents , Lareina Milambiling

Improving Deep Entity Resolution by Constraints , Soudeh Nilforoushan

Respiratory Pattern Analysis for COVID-19 Digital Screening Using AI Techniques , Annita Tahsin Priyoti

Extracting Microservice Dependencies Using Log Analysis , Andres O. Rodriguez Ishida

False Discovery Rate Analysis for Glycopeptide Identification , Shun Saito

Towards a Generalization of Fulton's Intersection Multiplicity Algorithm , Ryan Sandford

An Investigation Into Time Gazed At Traffic Objects By Drivers , Kolby R. Sarson

Exploring Artificial Intelligence (AI) Techniques for Forecasting Network Traffic: Network QoS and Security Perspectives , Ibrahim Mohammed Sayem

A Unified Representation and Deep Learning Architecture for Persuasive Essays in English , Muhammad Tawsif Sazid

Towards the development of a cost-effective Image-Sensing-Smart-Parking Systems (ISenSmaP) , Aakriti Sharma

Advances in the Automatic Detection of Optimization Opportunities in Computer Programs , Delaram Talaashrafi

Reputation-Based Trust Assessment of Transacting Service Components , Konstantinos Tsiounis

Fully Autonomous UAV Exploration in Confined and Connectionless Environments , Kirk P. Vander Ploeg

Three Contributions to the Theory and Practice of Optimizing Compilers , Linxiao Wang

Developing Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach , Wumian Wang

Predicting and Modifying Memorability of Images , Mohammad Younesi

Theses/Dissertations from 2021 2021

Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches , Mahtab Ahmed

A Physical Layer Framework for a Smart City Using Accumulative Bayesian Machine Learning , Razan E. AlFar

Load Balancing and Resource Allocation in Smart Cities using Reinforcement Learning , Aseel AlOrbani

Contrastive Learning of Auditory Representations , Haider Al-Tahan

Cache-Friendly, Modular and Parallel Schemes For Computing Subresultant Chains , Mohammadali Asadi

Protein Interaction Sites Prediction using Deep Learning , Sourajit Basak

Predicting Stock Market Sector Sentiment Through News Article Based Textual Analysis , William A. Beldman

Improving Reader Motivation with Machine Learning , Tanner A. Bohn

A Black-box Approach for Containerized Microservice Monitoring in Fog Computing , Shi Chang

Visualization and Interpretation of Protein Interactions , Dipanjan Chatterjee

A Framework for Characterising Performance in Multi-Class Classification Problems with Applications in Cancer Single Cell RNA Sequencing , Erik R. Christensen

Exploratory Search with Archetype-based Language Models , Brent D. Davis

Evolutionary Design of Search and Triage Interfaces for Large Document Sets , Jonathan A. Demelo

Building Effective Network Security Frameworks using Deep Transfer Learning Techniques , Harsh Dhillon

A Deep Topical N-gram Model and Topic Discovery on COVID-19 News and Research Manuscripts , Yuan Du

Automatic extraction of requirements-related information from regulatory documents cited in the project contract , Sara Fotouhi

Developing a Resource and Energy Efficient Real-time Delivery Scheduling Framework for a Network of Autonomous Drones , Gopi Gugan

A Visual Analytics System for Rapid Sensemaking of Scientific Documents , Amirreza Haghverdiloo Barzegar

Calibration Between Eye Tracker and Stereoscopic Vision System Employing a Linear Closed-Form Perspective-n-Point (PNP) Algorithm , Mohammad Karami

Fuzzy and Probabilistic Rule-Based Approaches to Identify Fault Prone Files , Piyush Kumar Korlepara

Parallel Arbitrary-precision Integer Arithmetic , Davood Mohajerani

A Technique for Evaluating the Health Status of a Software Module Using Process Metrics , . Ria

Visual Analytics for Performing Complex Tasks with Electronic Health Records , Neda Rostamzadeh

Predictive Model of Driver's Eye Fixation for Maneuver Prediction in the Design of Advanced Driving Assistance Systems , Mohsen Shirpour

A Generative-Discriminative Approach to Human Brain Mapping , Deepanshu Wadhwa

WesternAccelerator：Rapid Development of Microservices , Haoran Wei

A Lightweight and Explainable Citation Recommendation System , Juncheng Yin

Mitosis Detection from Pathology Images , Jinhang Zhang

Theses/Dissertations from 2020 2020

Visual Analytics of Electronic Health Records with a focus on Acute Kidney Injury , Sheikh S. Abdullah

Towards the Development of Network Service Cost Modeling-An ISP Perspective , Yasmeen Ali

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Computer Science and Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Refining the Machine Learning Pipeline for US-based Public Transit Systems , Jennifer Adorno

Insect Classification and Explainability from Image Data via Deep Learning Techniques , Tanvir Hossain Bhuiyan

Brain-Inspired Spatio-Temporal Learning with Application to Robotics , Thiago André Ferreira Medeiros

Evaluating Methods for Improving DNN Robustness Against Adversarial Attacks , Laureano Griffin

Analyzing Multi-Robot Leader-Follower Formations in Obstacle-Laden Environments , Zachary J. Hinnen

Secure Lightweight Cryptographic Hardware Constructions for Deeply Embedded Systems , Jasmin Kaur

A Psychometric Analysis of Natural Language Inference Using Transformer Language Models , Antonio Laverghetta Jr.

Graph Analysis on Social Networks , Shen Lu

Deep Learning-based Automatic Stereology for High- and Low-magnification Images , Hunter Morera

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai Ng Lugo

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai NG Lugo

Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery , Hye Seon Yi

Theses/Dissertations from 2022 2022

Towards High Performing and Reliable Deep Convolutional Neural Network Models for Typically Limited Medical Imaging Datasets , Kaoutar Ben Ahmed

Task Progress Assessment and Monitoring Using Self-Supervised Learning , Sainath Reddy Bobbala

Towards More Task-Generalized and Explainable AI Through Psychometrics , Alec Braynen

A Multiple Input Multiple Output Framework for the Automatic Optical Fractionator-based Cell Counting in Z-Stacks Using Deep Learning , Palak Dave

On the Reliability of Wearable Sensors for Assessing Movement Disorder-Related Gait Quality and Imbalance: A Case Study of Multiple Sclerosis , Steven Díaz Hernández

Securing Critical Cyber Infrastructures and Functionalities via Machine Learning Empowered Strategies , Tao Hou

Social Media Time Series Forecasting and User-Level Activity Prediction with Gradient Boosting, Deep Learning, and Data Augmentation , Fred Mubang

A Study of Deep Learning Silhouette Extractors for Gait Recognition , Sneha Oladhri

Analyzing Decision-making in Robot Soccer for Attacking Behaviors , Justin Rodney

Generative Spatio-Temporal and Multimodal Analysis of Neonatal Pain , Md Sirajus Salekin

Secure Hardware Constructions for Fault Detection of Lattice-based Post-quantum Cryptosystems , Ausmita Sarker

Adaptive Multi-scale Place Cell Representations and Replay for Spatial Navigation and Learning in Autonomous Robots , Pablo Scleidorovich

Predicting the Number of Objects in a Robotic Grasp , Utkarsh Tamrakar

Humanoid Robot Motion Control for Ramps and Stairs , Tommy Truong

Preventing Variadic Function Attacks Through Argument Width Counting , Brennan Ward

Theses/Dissertations from 2021 2021

Knowledge Extraction and Inference Based on Visual Understanding of Cooking Contents , Ahmad Babaeian Babaeian Jelodar

Efficient Post-Quantum and Compact Cryptographic Constructions for the Internet of Things , Rouzbeh Behnia

Efficient Hardware Constructions for Error Detection of Post-Quantum Cryptographic Schemes , Alvaro Cintas Canto

Using Hyper-Dimensional Spanning Trees to Improve Structure Preservation During Dimensionality Reduction , Curtis Thomas Davis

Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications , Arup Kanti Dey

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing , Hamza Elhamdadi

Automatic Detection of Vehicles in Satellite Images for Economic Monitoring , Cole Hill

Analysis of Contextual Emotions Using Multimodal Data , Saurabh Hinduja

Data-driven Studies on Social Networks: Privacy and Simulation , Yasanka Sameera Horawalavithana

Automated Identification of Stages in Gonotrophic Cycle of Mosquitoes Using Computer Vision Techniques , Sherzod Kariev

Exploring the Use of Neural Transformers for Psycholinguistics , Antonio Laverghetta Jr.

Secure VLSI Hardware Design Against Intellectual Property (IP) Theft and Cryptographic Vulnerabilities , Matthew Dean Lewandowski

Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages , Jamshidbek Mirzakhalov

Automated Wound Segmentation and Dimension Measurement Using RGB-D Image , Chih-Yun Pai

Constructing Frameworks for Task-Optimized Visualizations , Ghulam Jilani Abdul Rahim Quadri

Trilateration-Based Localization in Known Environments with Object Detection , Valeria M. Salas Pacheco

Recognizing Patterns from Vital Signs Using Spectrograms , Sidharth Srivatsav Sribhashyam

Recognizing Emotion in the Wild Using Multimodal Data , Shivam Srivastava

A Modular Framework for Multi-Rotor Unmanned Aerial Vehicles for Military Operations , Dante Tezza

Human-centered Cybersecurity Research — Anthropological Findings from Two Longitudinal Studies , Anwesh Tuladhar

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy , Troi André Williams

Human-centric Cybersecurity Research: From Trapping the Bad Guys to Helping the Good Ones , Armin Ziaie Tabari

Theses/Dissertations from 2020 2020

Classifying Emotions with EEG and Peripheral Physiological Data Using 1D Convolutional Long Short-Term Memory Neural Network , Rupal Agarwal

Keyless Anti-Jamming Communication via Randomized DSSS , Ahmad Alagil

Active Deep Learning Method to Automate Unbiased Stereology Cell Counting , Saeed Alahmari

Composition of Atomic-Obligation Security Policies , Yan Cao Albright

Action Recognition Using the Motion Taxonomy , Maxat Alibayev

Sentiment Analysis in Peer Review , Zachariah J. Beasley

Spatial Heterogeneity Utilization in CT Images for Lung Nodule Classication , Dmitrii Cherezov

Feature Selection Via Random Subsets Of Uncorrelated Features , Long Kim Dang

Unifying Security Policy Enforcement: Theory and Practice , Shamaria Engram

PsiDB: A Framework for Batched Query Processing and Optimization , Mehrad Eslami

Composition of Atomic-Obligation Security Policies , Danielle Ferguson

Algorithms To Profile Driver Behavior From Zero-permission Embedded Sensors , Bharti Goel

The Efficiency and Accuracy of YOLO for Neonate Face Detection in the Clinical Setting , Jacqueline Hausmann

Beyond the Hype: Challenges of Neural Networks as Applied to Social Networks , Anthony Hernandez

Privacy-Preserving and Functional Information Systems , Thang Hoang

Managing Off-Grid Power Use for Solar Fueled Residences with Smart Appliances, Prices-to-Devices and IoT , Donnelle L. January

Novel Bit-Sliced In-Memory Computing Based VLSI Architecture for Fast Sobel Edge Detection in IoT Edge Devices , Rajeev Joshi

Edge Computing for Deep Learning-Based Distributed Real-time Object Detection on IoT Constrained Platforms at Low Frame Rate , Lakshmikavya Kalyanam

Establishing Topological Data Analysis: A Comparison of Visualization Techniques , Tanmay J. Kotha

Machine Learning for the Internet of Things: Applications, Implementation, and Security , Vishalini Laguduva Ramnath

System Support of Concurrent Database Query Processing on a GPU , Hao Li

Deep Learning Predictive Modeling with Data Challenges (Small, Big, or Imbalanced) , Renhao Liu

Countermeasures Against Various Network Attacks Using Machine Learning Methods , Yi Li

Towards Safe Power Oversubscription and Energy Efficiency of Data Centers , Sulav Malla

Design of Support Measures for Counting Frequent Patterns in Graphs , Jinghan Meng

Automating the Classification of Mosquito Specimens Using Image Processing Techniques , Mona Minakshi

Models of Secure Software Enforcement and Development , Hernan M. Palombo

Functional Object-Oriented Network: A Knowledge Representation for Service Robotics , David Andrés Paulius Ramos

Lung Nodule Malignancy Prediction from Computed Tomography Images Using Deep Learning , Rahul Paul

Algorithms and Framework for Computing 2-body Statistics on Graphics Processing Units , Napath Pitaksirianan

Efficient Viewshed Computation Algorithms On GPUs and CPUs , Faisal F. Qarah

Relational Joins on GPUs for In-Memory Database Query Processing , Ran Rui

Micro-architectural Countermeasures for Control Flow and Misspeculation Based Software Attacks , Love Kumar Sah

Eﬃcient Forward-Secure and Compact Signatures for the Internet of Things (IoT) , Efe Ulas Akay Seyitoglu

Detecting Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure via Cough and Wheezing Sounds Using Smart-Phones and Machine Learning , Anthony Windmon

Toward Culturally Relevant Emotion Detection Using Physiological Signals , Khadija Zanna

Theses/Dissertations from 2019 2019

Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation , Sathyanarayanan Narasimhan Aakur

Empirical Analysis of a Cybersecurity Scoring System , Jaleel Ahmed

Phenomena of Social Dynamics in Online Games , Essa Alhazmi

A Machine Learning Approach to Predicting Community Engagement on Social Media During Disasters , Adel Alshehri

Interactive Fitness Domains in Competitive Coevolutionary Algorithm , ATM Golam Bari

Measuring Influence Across Social Media Platforms: Empirical Analysis Using Symbolic Transfer Entropy , Abhishek Bhattacharjee

A Communication-Centric Framework for Post-Silicon System-on-chip Integration Debug , Yuting Cao

Authentication and SQL-Injection Prevention Techniques in Web Applications , Cagri Cetin

Multimodal Emotion Recognition Using 3D Facial Landmarks, Action Units, and Physiological Data , Diego Fabiano

Robotic Motion Generation by Using Spatial-Temporal Patterns from Human Demonstrations , Yongqiang Huang

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Home > School, College, or Department > MCECS > Computer Science > Dissertations and Theses

Computer Science Dissertations and Theses

Theses/dissertations from 2024 2024.

MmWave RAT Optimization: MAC Layer Initial Access Design and Transport Layer Integration , Suresh Srinivasan (Dissertation)

Theses/Dissertations from 2023 2023

Seeing in the Dark: Towards Robust Pedestrian Detection at Nighttime , Afnan Althoupety (Dissertation)

A Deep Hierarchical Variational Autoencoder for World Models in Complex Reinforcement Learning Environments , Sriharshitha Ayyalasomayajula (Thesis)

Toward Efficient Rendering: A Neural Network Approach , Qiqi Hou (Dissertation)

Energy Auction with Non-Relational Persistence , Michael Ramez Howard (Thesis)

Implementing a Functional Logic Programming Language via the Fair Scheme , Andrew Michael Jost (Dissertation)

Multi-Agent Deep Reinforcement Learning for Radiation Localization , Benjamin Scott Totten (Thesis)

Theses/Dissertations from 2022 2022

Using Intrinsically-Typed Definitional Interpreters to Verify Compiler Optimizations in a Monadic Intermediate Language , Dani Barrack (Thesis)

An Automated Zoom Class Session Analysis Tool to Improve Education , Jack Arlo Cannon II (Thesis)

Scaling EPA-RIMM with Multicore System Management Interrupt Handlers , Alexander K. Freed (Thesis)

Unpaired Style Transfer Conditional Generative Adversarial Network for Scanned Document Generation , David Jonathan Hawbaker (Thesis)

Toward Analyzing the Diversity of Extractive Summaries , Aaron David Hudson (Thesis)

Making Curry with Rice: An Optimizing Curry Compiler , Steven Libby (Dissertation)

Domain Knowledge as Motion-Aware Inductive Bias for Deep Video Synthesis: Two Case Studies , Long Mai (Dissertation)

Theses/Dissertations from 2021 2021

Efficient Neuromorphic Algorithms for Gamma-Ray Spectrum Denoising and Radionuclide Identification , Merlin Phillip Carson (Thesis)

Storing Intermediate Results in Space and Time: SQL Graphs and Block Referencing , Basem Ibrahim Elazzabi (Dissertation)

Automated Test Generation for Validating SystemC Designs , Bin Lin (Dissertation)

Forecasting Optimal Parameters of the Broken Wing Butterfly Option Strategy Using Differential Evolution , David Munoz Constantine (Thesis)

Situate: An Agent-Based System for Situation Recognition , Max Henry Quinn (Dissertation)

Theses/Dissertations from 2020 2020

Multiple Diagram Navigation , Hisham Benotman (Dissertation)

Smart Contract Vulnerabilities on the Ethereum Blockchain: a Current Perspective , Daniel Steven Connelly (Thesis)

Extensible Performance-Aware Runtime Integrity Measurement , Brian G. Delgado (Dissertation)

Novel View Synthesis - a Neural Network Approach , Hoang Le (Dissertation)

Exploring the Potential of Sparse Coding for Machine Learning , Sheng Yang Lundquist (Dissertation)

Workflow Critical Path: a Data-Oriented Path Metric for Holistic HPC Workflows , Daniel D. Nguyen (Thesis)

Novel View Synthesis in Time and Space , Simon Niklaus (Dissertation)

Balancing Security, Performance and Deployability in Encrypted Search , David Joel Pouliot (Dissertation)

Theses/Dissertations from 2019 2019

A Secure Anti-Counterfeiting System using Near Field Communication, Public Key Cryptography, Blockchain, and Bayesian Games , Naif Saeed Alzahrani (Dissertation)

Spectral Clustering for Electrical Phase Identification Using Advanced Metering Infrastructure Voltage Time Series , Logan Blakely (Thesis)

Local Radiance , Scott Peter Britell (Dissertation)

Correct-by-Construction Typechecking with Scope Graphs , Katherine Imhoff Casamento (Thesis)

Versatile Binary-level Concolic Testing , Bo Chen (Dissertation)

Crumpled and Abraded Encryption: Implementation and Provably Secure Construction , Scott Sherlock Griffy (Thesis)

Knowing Without Knowing: Real-Time Usage Identification of Computer Systems , Leila Mohammed Hawana (Thesis)

Design and Experimental Evaluation of DeepMarket: an Edge Computing Marketplace with Distributed TensorFlow Execution Capability , Soyoung Kim (Thesis)

Localizing Little Landmarks with Transfer Learning , Sharad Kumar (Thesis)

Context-Aware Wi-Fi Infrastructure-based Indoor Positioning Systems , Huy Phuong Tran (Dissertation)

Theses/Dissertations from 2018 2018

Bounding Box Improvement with Reinforcement Learning , Andrew Lewis Cleland (Thesis)

Sensing Building Structure Using UWB Radios for Disaster Recovery , Jeong Eun Lee (Dissertation)

Annotation-Enabled Interpretation and Analysis of Time-Series Data , Niveditha Venugopal (Thesis)

EPA-RIMM-V: Efficient Rootkit Detection for Virtualized Environments , Tejaswini Ajay Vibhute (Thesis)

Theses/Dissertations from 2017 2017

Improved Scoring Models for Semantic Image Retrieval Using Scene Graphs , Erik Timothy Conser (Thesis)

Refining Bounding-Box Regression for Object Localization , Naomi Lynn Dickerson (Thesis)

Fully Generic Programming Over Closed Universes of Inductive-Recursive Types , Larry Diehl (Dissertation)

Communicating at Terahertz Frequencies , Farnoosh Moshirfatemi (Dissertation)

Designing In-Headset Authoring Tools for Virtual Reality Video , Cuong Nguyen (Dissertation)

Certifying Loop Pipelining Transformations in Behavioral Synthesis , Disha Puri (Dissertation)

Power-Aware Datacenter Networking and Optimization , Qing Yi (Dissertation)

Theses/Dissertations from 2016 2016

Identifying Relationships between Scientific Datasets , Abdussalam Alawini (Dissertation)

Information Representation and Computation of Spike Trains in Reservoir Computing Systems with Spiking Neurons and Analog Neurons , Amin Almassian (Thesis)

Investigations of an "Objectness" Measure for Object Localization , Lewis Richard James Coates (Thesis)

Image Stitching: Handling Parallax, Stereopsis, and Video , Fan Zhang (Dissertation)

Theses/Dissertations from 2015 2015

Novel Methods for Learning and Adaptation in Chemical Reaction Networks , Peter Banda (Dissertation)

Post-silicon Functional Validation with Virtual Prototypes , Kai Cong (Dissertation)

Novel Cryptographic Primitives and Protocols for Censorship Resistance , Kevin Patrick Dyer (Dissertation)

Hardware/Software Interface Assurance with Conformance Checking , Li Lei (Dissertation)

Leveraging Contextual Relationships Between Objects for Localization , Clinton Leif Olson (Thesis)

The Performance of Random Prototypes in Hierarchical Models of Vision , Kendall Lee Stewart (Thesis)

Tweakable Ciphers: Constructions and Applications , Robert Seth Terashima (Dissertation)

Scalable Equivalence Checking for Behavioral Synthesis , Zhenkun Yang (Dissertation)

Theses/Dissertations from 2014 2014

The Nax Language: Unifying Functional Programming and Logical Reasoning in a Language based on Mendler-style Recursion Schemes and Term-indexed Types , Ki Yung Ahn (Dissertation)

Using Spammers' Computing Resources for Volunteer Computing , Thai Le Quy Bui (Thesis)

Towards Constructing Interactive Virtual Worlds , Francis Chang (Dissertation)

System-wide Performance Analysis for Virtualization , Deron Eugene Jensen (Thesis)

Advances in Piecewise Smooth Image Reconstruction , Ralf Juengling (Dissertation)

Interpretable Machine Learning and Sparse Coding for Computer Vision , Will Landecker (Dissertation)

Optimizing Data Movement in Hybrid Analytic Systems , Patrick Michael Leyshock (Dissertation)

Ranked Similarity Search of Scientific Datasets: An Information Retrieval Approach , Veronika Margaret Megler (Dissertation)

Using GIST Features to Constrain Search in Object Detection , Joanna Browne Solmon (Thesis)

The Role of Prototype Learning in Hierarchical Models of Vision , Michael David Thomure (Dissertation)

Theses/Dissertations from 2013 2013

Object Detection and Recognition in Natural Settings , George William Dittmar (Thesis)

Trust-but-Verify: Guaranteeing the Integrity of User-generated Content in Online Applications , Akshay Dua (Dissertation)

Equivalence Checking for High-Assurance Behavioral Synthesis , Kecheng Hao (Dissertation)

Type Classes and Instance Chains: A Relational Approach , John Garrett Morris (Dissertation)

Theses/Dissertations from 2012 2012

Using Dataflow Optimization Techniques with a Monadic Intermediate Language , Justin George Bailey (Thesis)

A Survey and Analysis of Solutions to the Oblivious Memory Access Problem , Erin Elizabeth Chapman (Thesis)

A Data-Descriptive Feedback Framework for Data Stream Management Systems , Rafael J. Fernández Moctezuma (Dissertation)

Extending Relativistic Programming to Multiple Writers , Philip William Howard (Dissertation)

The Basic Scheme for the Evaluation of Functional Logic Programs , Arthur Peters (Thesis)

The Link Between Image Segmentation and Image Recognition , Karan Sharma (Thesis)

Relativistic Causal Ordering A Memory Model for Scalable Concurrent Data Structures , Josh Triplett (Dissertation)

Theses/Dissertations from 2011 2011

Conceptual Modeling of Data with Provenance , David William Archer (Dissertation)

Low-latency Estimates for Window-Aggregate Queries over Data Streams , Amit Bhat (Thesis)

Information Processing in Two-Dimensional Cellular Automata , Martin Cenek (Dissertation)

Scalable and Efficient Tasking for Dynamic Sensor Networks , Thanh Xuan Dang (Dissertation)

On the Effect of Topology on Learning and Generalization in Random Automata Networks , Alireza Goudarzi (Thesis)

HOLCF '11: A Definitional Domain Theory for Verifying Functional Programs , Brian Charles Huffman (Dissertation)

A Functional Approach to Memory-Safe Operating Systems , Rebekah Leslie (Dissertation)

Factoring Semiprimes Using PG2N Prime Graph Multiagent Search , Keith Eirik Wilson (Thesis)

High Speed Wireless Networking for 60GHz , Candy Yiu (Dissertation)

Theses/Dissertations from 2010 2010

Extensible Scheduling in a Haskell-based Operating System , Kenneth William Graunke (Thesis)

Addressing Automated Adversaries of Network Applications , Edward Leo Kaiser (Dissertation)

An Automata-Theoretic Approach to Hardware/Software Co-verification , Juncao Li (Dissertation)

Practical Type Inference for the GADT Type System , Chuan-kai Lin (Dissertation)

Scalable event tracking on high-end parallel systems , Kathryn Marie Mohror (Dissertation)

Performance Analysis of Hybrid CPU/GPU Environments , Michael Shawn Smith (Thesis)

Theses/Dissertations from 2009 2009

Computational Techniques for Reducing Spectra of the Giant Planets in Our Solar System , Holly L. Grimes (Thesis)

Programmer Friendly Refactoring Tools , Emerson Murphy-Hill (Dissertation)

A Framework for Superimposed Applications : Techniques to Represent, Access, Transform, and Interchange Bi-level Information , Sudarshan Srivivasa Murthy (Dissertation)

Graphical User Interfaces as Updatable Views , James Felger Terwilliger (Dissertation)

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Distinguished Dissertations in Computer Science

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The Conference of Professors of Computer Science (CPCS), in conjunction with the British Computer Society, selects annually for publication a few of the best British PhD dissertations in computer science. Its aim is to make more visible the significant British contribution to this field, and to provide a model for future students. At most three or four dissertations are selected for publication each year. They have a high standard of exposition and place results particularly clearly in the context of computer science. Computer scientists with significantly different interests will be able to grasp the essentials of each book and use it as a means of entry to an unfamiliar research topic.

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10 results in Distinguished Dissertations in Computer Science

Axiomatic Domain Theory in Categories of Partial Maps

Marcelo P. Fiore
Published online: 23 November 2009 Print publication: 08 August 1996
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View description Axiomatic categorical domain theory is crucial for understanding the meaning of programs and reasoning about them. This book is the first systematic account of the subject and studies mathematical structures suitable for modelling functional programming languages in an axiomatic (i.e. abstract) setting. In particular, the author develops theories of partiality and recursive types and applies them to the study of the metalanguage FPC; for example, enriched categorical models of the FPC are defined. Furthermore, FPC is considered as a programming language with a call-by-value operational semantics and a denotational semantics defined on top of a categorical model. To conclude, for an axiomatisation of absolute non-trivial domain-theoretic models of FPC, operational and denotational semantics are related by means of computational soundness and adequacy results. To make the book reasonably self-contained, the author includes an introduction to enriched category theory.

The Map-Building and Exploration Strategies of a Simple Sonar-Equipped Mobile Robot

An Experimental, Quantitative Evaluation
Published online: 05 March 2012 Print publication: 26 July 1996
View description There are two radically different approaches to robot navigation: the first is to use a map of the robot's environment; the second uses a set of action reflexes to enable a robot to react rapidly to local sensory information. Hybrid approaches combining features of both also exist. This book is the first to propose a method for evaluating the different approaches that shows how to decide which is the most appropriate for a given situation. It begins by describing a complete implementation of a mobile robot including sensor modelling, map–building (a feature–based map and a grid–based free–space map), localisation, and path–planning. Exploration strategies are then tested experimentally in a range of environments and starting positions. The author shows the most promising results are observed from hybrid exploration strategies which combine the robustness of reactive navigation and the directive power of map–based strategies.

A Compositional Approach to Performance Modelling

Jane Hillston
Published online: 24 November 2009 Print publication: 13 June 1996
View description This is the first book presenting a stochastic extension of process algebra, PEPA; this is shown to be suitable for specifying a Markov process, which can then be applied to performance modelling. The method, which is illustrated with case studies taken from the area of communication systems, can readily be used to construct a variety of models that can be analysed using standard numerical techniques. One of the major advantages of PEPA over the standard methods for specifying stochastic performance models is the inherent apparatus for reasoning about the structure and behaviour of models. In the later chapters this apparatus is exploited to define four equivalence relations over PEPA components. Each of these notions of equivalence has intrinsic interest from a process algebra perspective. However, they are also demonstrated to be useful in a performance modelling context. To conclude the book, a section has been added surveying recent results in the area and discussing open questions.

Affine Analysis of Image Sequences

Larry S. Shapiro
Published online: 18 December 2009 Print publication: 13 July 1995
View description Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then computed via 'affine epipolar geometry', and 'affine structure' is used to generate alternative views of the object and fill in partial views. The use of all available features (over multiple frames) and the incorporation of statistical noise properties substantially improves existing algorithms, giving greater reliability and reduced noise sensitivity.

Qualified Types

Theory and Practice
Mark P. Jones
Published online: 05 May 2010 Print publication: 03 November 1994
View description This book describes the use of qualified types to provide a general framework for the combination of polymorphism and overloading. For example, qualified types can be viewed as a generalization of type classes in the functional language Haskell and the theorem prover Isabelle. These in turn are extensions of equality types in Standard ML. Other applications of qualified types include extensible records and subtyping. Using a general formulation of qualified types, the author extends the Damas/Milner type inference algorithm to support qualified types, which in turn specifies the set of all possible types for any term. In addition, he describes a new technique for establishing suitable coherence conditions that guarantee the same semantics for all possible translations of a given term. Practical issues that arise in concrete implementations are also discussed, concentrating in particular on the implementation of overloading in Haskell and Gofer, a small functional programming system developed by the author.

Specification and Proof in Real Time CSP

Published online: 04 August 2010 Print publication: 20 May 1993
View description This book was first published in 1993. Computing systems are becoming highly complex, harder to understand, and therefore more prone to failure. Where such systems control aircraft for example, system failure could have disastrous consequences. It is important therefore that we are able to employ mathematical techniques to specify the behaviour or safety critical systems. This thesis uses the theory of Communicating Sequential Processes (CSP) to show how a real-lime system may be specified. Included is a case study in which a local area network protocol is described at two levels of abstraction, and a general method 14 structuring CSP descriptions of layered protocols is given.

Efficient Algorithms for Listing Combinatorial Structures

Leslie Ann Goldberg
Published online: 14 January 2010 Print publication: 22 April 1993
View description First published in 1993, this thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members? What general methods are useful for listing combinatorial structures? How can these be applied to those families which are of interest to theoretical computer scientists and combinatorialists? Amongst those families considered are unlabelled graphs, first order one properties, Hamiltonian graphs, graphs with cliques of specified order, and k-colourable graphs. Some related work is also included, which compares the listing problem with the difficulty of solving the existence problem, the construction problem, the random sampling problem, and the counting problem. In particular, the difficulty of evaluating Pólya's cycle polynomial is demonstrated.

Logic Programming

Operational Semantics and Proof Theory
James H. Andrews
Published online: 23 November 2009 Print publication: 17 December 1992
View description Dr Andrews here provides a homogeneous treatment of the semantics (operational and logical) of both theoretical and practical logic programming languages. He shows how the rift between theory and practice in logic programming can be bridged. This is achieved by precisely characterizing the way in which 'depth-first' search for solutions to a logical formula - the usual strategy in most practical languages - is incomplete. Languages that perform 'breadth-first' searches reflect more closely the theory underlying logic programming languages. Researchers interested in logic programming or semantics, as well as artificial intelligence search strategies, will want to consult this book as the only source for some essential and new ideas in the area.

Three-Dimensional Integrated Circuit Layout

A. C. Harter
Published online: 05 May 2010 Print publication: 28 November 1991
View description First published in 1991, this thesis concentrates upon the design of three-dimensional, rather than the traditional two-dimensional, circuits. The theory behind such circuits is presented in detail, together with experimental results. Winner of the Distinguished Dissertation in Computer Science award, this work will prove invaluable to both designers and hardware engineers involved in the development of practical three-dimensional integrated circuits.

Project Factorisations in Partial Evaluation

John Launchbury
Published online: 04 August 2010 Print publication: 24 October 1991
View description Programming frequently requires that problems are broken down into subproblems and then each subproblem solved independently. These solutions may then be combined to provide a solution to the original problem. Partial evaluation is a serious attempt to tackle this issue, allowing the programmer to write programs in a highly interpretive style without paying the price in efficiency. This thesis covers the theory and practice behind practical evaluation.

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Home > Engineering > Computer Science > Computer Science Graduate Projects

Computer Science Graduate Projects and Theses

Theses/dissertations from 2023 2023.

High-Performance Domain-Specific Library for Hydrologic Data Processing , Kalyan Bhetwal

Verifying Data Provenance During Workflow Execution for Scientific Reproducibility , Rizbanul Hasan

Remote Sensing to Advance Understanding of Snow-Vegetation Relationships and Quantify Snow Depth and Snow Water Equivalent , Ahmad Hojatimalekshah

Exploring the Capability of a Self-Supervised Conditional Image Generator for Image-to-Image Translation without Labeled Data: A Case Study in Mobile User Interface Design , Hailee Kiesecker

Fake News Detection Using Narrative Content and Discourse , Hongmin Kim

Anomaly Detection Using Graph Neural Network , Bishal Lakha

Sparse Format Conversion and Code Synthesis , Tobi Goodness Popoola

Portable Sparse Polyhedral Framework Code Generation Using Multi Level Intermediate Representation , Aaron St. George

Severity Measures for Assessing Error in Automatic Speech Recognition , Ryan Whetten

Theses/Dissertations from 2022 2022

Improved Computational Prediction of Function and Structural Representation of Self-Cleaving Ribozymes with Enhanced Parameter Selection and Library Design , James D. Beck

Meshfree Methods for PDEs on Surfaces , Andrew Michael Jones

Deep Learning of Microstructures , Amir Abbas Kazemzadeh Farizhandi

Long-Term Trends in Extreme Environmental Events with Changepoint Detection , Mintaek Lee

Structure Aware Smart Encoding and Decoding of Information in DNA , Shoshanna Llewellyn

Towards Making Transformer-Based Language Models Learn How Children Learn , Yousra Mahdy

Ontology-Based Formal Approach for Safety and Security Verification of Industrial Control Systems , Ramesh Neupane

Improving Children's Authentication Practices with Respect to Graphical Authentication Mechanism , Dhanush Kumar Ratakonda

Hate Speech Detection Using Textual and User Features , Rohan Raut

Automated Detection of Sockpuppet Accounts in Wikipedia , Mostofa Najmus Sakib

Characterization and Mitigation of False Information on the Web , Anu Shrestha

Sinusoidal Projection for 360° Image Compression and Triangular Discrete Cosine Transform Impact in the JPEG Pipeline , Iker Vazquez Lopez

Theses/Dissertations from 2021 2021

Training Wheels for Web Search: Multi-Perspective Learning to Rank to Support Children's Information Seeking in the Classroom , Garrett Allen

Fair and Efficient Consensus Protocols for Secure Blockchain Applications , Golam Dastoger Bashar

Why Don't You Act Your Age?: Recognizing the Stereotypical 8-12 Year Old Searcher by Their Search Behavior , Michael Green

Ensuring Consistency and Efficiency of the Incremental Unit Network in a Distributed Architecture , Mir Tahsin Imtiaz

Modeling Real and Fake News Sharing in Social Networks , Abishai Joy

Modeling and Analyzing Users' Privacy Disclosure Behavior to Generate Personalized Privacy Policies , A.K.M. Nuhil Mehdy

Into the Unknown: Exploration of Search Engines' Responses to Users with Depression and Anxiety , Ashlee Milton

Generating Test Inputs from String Constraints with an Automata-Based Solver , Marlin Roberts

A Case Study in Representing Scientific Applications ( GeoAc ) Using the Sparse Polyhedral Framework , Ravi Shankar

Actors for the Internet of Things , Arjun Shukla

Theses/Dissertations from 2020 2020

Towards Unifying Grounded and Distributional Semantics Using the Words-as-Classifiers Model of Lexical Semantics , Stacy Black

Improving Scientist Productivity, Architecture Portability, and Performance in ParFlow , Michael Burke

Polyhedral+Dataflow Graphs , Eddie C. Davis

Improving Spellchecking for Children: Correction and Design , Brody Downs

A Collection of Fast Algorithms for Scalar and Vector-Valued Data on Irregular Domains: Spherical Harmonic Analysis, Divergence-Free/Curl-Free Radial Basis Functions, and Implicit Surface Reconstruction , Kathryn Primrose Drake

Privacy-Preserving Protocol for Atomic Swap Between Blockchains , Kiran Gurung

Unsupervised Structural Graph Node Representation Learning , Mikel Joaristi

Detecting Undisclosed Paid Editing in Wikipedia , Nikesh Joshi

Do You Feel Me?: Learning Language from Humans with Robot Emotional Displays , David McNeill

Obtaining Real-World Benchmark Programs from Open-Source Repositories Through Abstract-Semantics Preserving Transformations , Maria Anne Rachel Paquin

Content Based Image Retrieval (CBIR) for Brand Logos , Enjal Parajuli

A Resilience Metric for Modern Power Distribution Systems , Tyler Bennett Phillips

Theses/Dissertations from 2019 2019

Edge-Assisted Workload-Aware Image Processing System , Anil Acharya

MINOS: Unsupervised Netflow-Based Detection of Infected and Attacked Hosts, and Attack Time in Large Networks , Mousume Bhowmick

Deviant: A Mutation Testing Tool for Solidity Smart Contracts , Patrick Chapman

Querying Over Encrypted Databases in a Cloud Environment , Jake Douglas

A Hybrid Model to Detect Fake News , Indhumathi Gurunathan

Suitability of Finite State Automata to Model String Constraints in Probablistic Symbolic Execution , Andrew Harris

UNICORN Framework: A User-Centric Approach Toward Formal Verification of Privacy Norms , Rezvan Joshaghani

Detection and Countermeasure of Saturation Attacks in Software-Defined Networks , Samer Yousef Khamaiseh

Secure Two-Party Protocol for Privacy-Preserving Classification via Differential Privacy , Manish Kumar

Application-Specific Memory Subsystem Benchmarking , Mahesh Lakshminarasimhan

Multilingual Information Retrieval: A Representation Building Perspective , Ion Madrazo

Improved Study of Side-Channel Attacks Using Recurrent Neural Networks , Muhammad Abu Naser Rony Chowdhury

Investigating the Effects of Social and Temporal Dynamics in Fitness Games on Children's Physical Activity , Ankita Samariya

BullyNet: Unmasking Cyberbullies on Social Networks , Aparna Sankaran

FALCON: Framework for Anomaly Detection In Industrial Control Systems , Subin Sapkota

Investigating Semantic Properties of Images Generated from Natural Language Using Neural Networks , Samuel Ward Schrader

Incremental Processing for Improving Conversational Grounding in a Chatbot , Aprajita Shukla

Estimating Error and Bias of Offline Recommender System Evaluation Results , Mucun Tian

Theses/Dissertations from 2018 2018

Leveraging Tiled Display for Big Data Visualization Using D3.js , Ujjwal Acharya

Fostering the Retrieval of Suitable Web Resources in Response to Children's Educational Search Tasks , Oghenemaro Deborah Anuyah

Privacy-Preserving Genomic Data Publishing via Differential Privacy , Tanya Khatri

Injecting Control Commands Through Sensory Channel: Attack and Defense , Farhad Rasapour

Strong Mutation-Based Test Generation of XACML Policies , Roshan Shrestha

Performance, Scalability, and Robustness in Distributed File Tree Copy , Christopher Robert Sutton

Using DNA For Data Storage: Encoding and Decoding Algorithm Development , Kelsey Suyehira

Detecting Saliency by Combining Speech and Object Detection in Indoor Environments , Kiran Thapa

Theses/Dissertations from 2017 2017

Identifying Restaurants Proposing Novel Kinds of Cuisines: Using Yelp Reviews , Haritha Akella

Editing Behavior Analysis and Prediction of Active/Inactive Users in Wikipedia , Harish Arelli

CloudSkulk: Design of a Nested Virtual Machine Based Rootkit-in-the-Middle Attack , Joseph Anthony Connelly

Predicting Friendship Strength in Facebook , Nitish Dhakal

Privacy-Preserving Trajectory Data Publishing via Differential Privacy , Ishita Dwivedi

Cultivating Community Interactions in Citizen Science: Connecting People to Each Other and the Environment , Bret Allen Finley

Uncovering New Links Through Interaction Duration , Laxmi Amulya Gundala

Variance: Secure Two-Party Protocol for Solving Yao's Millionaires' Problem in Bitcoin , Joshua Holmes

A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases , Akshay Kansal

Integrity Coded Databases: Ensuring Correctness and Freshness of Outsourced Databases , Ujwal Karki

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display , Yuan Li

The Effects of Pair-Programming in a High School Introductory Computer Science Class , Ken Manship

Towards Automatic Repair of XACML Policies , Shuai Peng

Identification of Unknown Landscape Types Using CNN Transfer Learning , Ashish Sharma

Hand Gesture Recognition for Sign Language Transcription , Iker Vazquez Lopez

Learning to Code Music : Development of a Supplemental Unit for High School Computer Science , Kelsey Wright

Theses/Dissertations from 2016 2016

Identification of Small Endogenous Viral Elements within Host Genomes , Edward C. Davis Jr.

When the System Becomes Your Personal Docent: Curated Book Recommendations , Nevena Dragovic

Security Testing with Misuse Case Modeling , Samer Yousef Khamaiseh

Estimating Length Statistics of Aggregate Fried Potato Product via Electromagnetic Radiation Attenuation , Jesse Lovitt

Towards Multipurpose Readability Assessment , Ion Madrazo

Evaluation of Topic Models for Content-Based Popularity Prediction on Social Microblogs , Axel Magnuson

CEST: City Event Summarization using Twitter , Deepa Mallela

Developing an ABAC-Based Grant Proposal Workflow Management System , Milson Munakami

Phoenix and Hive as Alternatives to RDBMS , Diana Ornelas

Massively Parallel Algorithm for Solving the Eikonal Equation on Multiple Accelerator Platforms , Anup Shrestha

A Certificateless One-Way Group Key Agreement Protocol for Point-to-Point Email Encryption , Srisarguru Sridhar

Dynamic Machine Level Resource Allocation to Improve Tasking Performance Across Multiple Processes , Richard Walter Thatcher

Theses/Dissertations from 2015 2015

Developing an Application for Evolutionary Search for Computational Models of Cellular Development , Nicolas Scott Cornia

Accelerated Radar Signal Processing in Large Geophysical Datasets , Ravi Preesha Geetha

Integrity Coded Databases (ICDB) – Protecting Integrity for Outsourced Databases , Archana Nanjundarao

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Home > Sciences > Computer Science > ETDs

Computer Science Theses & Dissertations

Theses and dissertations published by graduate students in the Department of Computer Science, College of Sciences, Old Dominion University, since Fall 2016 are available in this collection. Backfiles of all dissertations (and some theses) have also been added.

In late Fall 2023 or Spring 2024, all theses will be digitized and available here. In the meantime, consult the Library Catalog to find older items in print.

Theses/Dissertations from 2024 2024

Thesis: Study of Deep Learning Models to Classify Nasa’s Kepler Light Curves , Heena Minnich

Theses/Dissertations from 2023 2023

Dissertation: Inverse Mappers for QCD Global Analysis , Manal Almaeen

Thesis: Assessing the Prevalence and Archival Rate of URIs to Git Hosting Platforms in Scholarly Publications , Emily Escamilla

Thesis: Supporting Account-based Queries for Archived Instagram Posts , Himarsha R. Jayanetti

Dissertation: Detecting Malware With Securedeep Accelerator via Processor Side-Channel Fingerprinting for Internet of Things , Zhuoran Li

Dissertation: Tracing and Segmentation of Molecular Patterns in 3-Dimensional Cryo-ET/EM Density Maps Through Algorithmic Image Processing and Deep Learning-Based Techniques , Salim Sazzed

Dissertation: Towards Intelligent Runtime Framework for Distributed Heterogeneous Systems , Polykarpos Thomadakis

Theses/Dissertations from 2022 2022

Dissertation: Machine Learning-Based Event Generator , Yasir Alanazi

Thesis: Using Ensemble Learning Techniques to Solve the Blind Drift Calibration Problem , Devin Scott Drake

Dissertation: A Relevance Model for Threat-Centric Ranking of Cybersecurity Vulnerabilities , Corren G. McCoy

Dissertation: Evaluation of Generative Models for Predicting Microstructure Geometries in Laser Powder Bed Fusion Additive Manufacturing , Andy Ramlatchan

Thesis: TransParsCit: A Transformer-Based Citation Parser Trained on Large-Scale Synthesized Data , MD Sami Uddin

Dissertation: Towards Privacy and Security Concerns of Adversarial Examples in Deep Hashing Image Retrieval , Yanru Xiao

Theses/Dissertations from 2021 2021

Dissertation: MOVE: Mobile Observers Variants and Extensions , Ryan Florin

Dissertation: Improving Collection Understanding for Web Archives with Storytelling: Shining Light Into Dark and Stormy Archives , Shawn M. Jones

Dissertation: A Unified Framework for Parallel Anisotropic Mesh Adaptation , Christos Tsolakis

Theses/Dissertations from 2020 2020

Dissertation: MementoMap: A Web Archive Profiling Framework for Efficient Memento Routing , Sawood Alam

Dissertation: A Framework for Verifying the Fixity of Archived Web Resources , Mohamed Aturban

Thesis: Parallelization of the Advancing Front Local Reconnection Mesh Generation Software Using a Pseudo-Constrained Parallel Data Refinement Method , Kevin Mark Garner Jr.

Dissertation: Towards Dynamic Vehicular Clouds , Aida Ghazizadeh

Dissertation: Bootstrapping Web Archive Collections From Micro-Collections in Social Media , Alexander C. Nwala

Dissertation: Automatic Linear and Curvilinear Mesh Generation Driven by Validity Fidelity and Topological Guarantees , Jing Xu

Theses/Dissertations from 2019 2019

Dissertation: Expanding the Usage of Web Archives by Recommending Archived Webpages Using Only the URI , Lulwah M. Alkwai

Dissertation: Highly Accurate Fragment Library for Protein Fold Recognition , Wessam Elhefnawy

Dissertation: Scalable Parallel Delaunay Image-to-Mesh Conversion for Shared and Distributed Memory Architectures , Daming Feng

Dissertation: Aggregating Private and Public Web Archives Using the Mementity Framework , Matthew R. Kelly

Thesis: Enhancing Portability in High Performance Computing: Designing Fast Scientific Code with Longevity , Jason Orender

Thesis: Novel Use of Neural Networks to Identify and Detect Electrical Infrastructure Performance , Evan Pierre Savaria

Theses/Dissertations from 2018 2018

Dissertation: New Methods to Improve Protein Structure Modeling , Maha Abdelrasoul

Dissertation: Applying Machine Learning to Advance Cyber Security: Network Based Intrusion Detection Systems , Hassan Hadi Latheeth AL-Maksousy

Thesis: To Relive the Web: A Framework for the Transformation and Archival Replay of Web Pages , John Andrew Berlin

Thesis: Supporting Big Data at the Vehicular Edge , Lloyd Decker

Thesis: Deep Learning for Segmentation Of 3D Cryo-EM Images , Devin Reid Haslam

Dissertation: FlexStream: SDN-Based Framework for Programmable and Flexible Adaptive Video Streaming , Ibrahim Ben Mustafa

Thesis: Novel Technique for Gait Analysis Using Two Waist Mounted Gyroscopes , Ahmed Nasr

Dissertation: Leveraging Resources on Anonymous Mobile Edge Nodes , Ahmed Salem

Theses/Dissertations from 2017 2017

Dissertation: SenSys: A Smartphone-Based Framework for ITS applications , Abdulla Ahmed Alasaadi

Dissertation: ItsBlue: A Distributed Bluetooth-Based Framework for Intelligent Transportation Systems , Ahmed Awad Alghamdi

Dissertation: Finite Element Modeling Driven by Health Care and Aerospace Applications , Fotios Drakopoulos

Dissertation: Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures , Kamesh Arumugam Karunanithi

Thesis: Multi-GPU Accelerated High-Fidelity Simulations of Beam-Beam Effects in Particle Colliders , Naga Sai Ravi Teja Majeti

Theses/Dissertations from 2016 2016

Dissertation: Using Web Archives to Enrich the Live Web Experience Through Storytelling , Yasmin AlNoamany

Thesis: Magnopark, Smart Parking Detection Based on Cellphone Magnetic Sensor , Maryam Arab

Dissertation: Scripts in a Frame: A Framework for Archiving Deferred Representations , Justin F. Brunelle

Dissertation: Machine Learning Methods for Brain Image Analysis , Ahmed Fakhry

Dissertation: Novel Monte Carlo Methods for Large-Scale Linear Algebra Operations , Hao Ji

Dissertation: Machine Learning Methods for Medical and Biological Image Computing , Rongjian Li

Dissertation: Toward Open and Programmable Wireless Network Edge , Mostafa Uddin

Thesis: An Optimized Multiple Right-Hand Side Dslash Kernel for Intel Xeon Phi , Aaron Walden

Dissertation: Towards Aggregating Time-Discounted Information in Sensor Networks , Xianping Wang

Dissertation: A Computational Framework for Learning from Complex Data: Formulations, Algorithms, and Applications , Wenlu Zhang

Theses/Dissertations from 2015 2015

Dissertation: Efficient Algorithms for Prokaryotic Whole Genome Assembly and Finishing , Abhishek Biswas

Dissertation: De Novo Protein Structure Modeling and Energy Function Design , Lin Chen

Dissertation: High Performance Large Graph Analytics by Enhancing Locality , Naga Shailaja Dasari

Thesis: Avoiding Spoilers on Mediawiki Fan Sites Using Memento , Shawn M. Jones

Dissertation: Energy Harvesting-Aware Design for Wireless Nanonetworks , Shahram Mohrehkesh

Thesis: Parallel Two-Dimensional Unstructured Anisotropic Delaunay Mesh Generation for Aerospace Applications , Juliette Kelly Pardue

Dissertation: Detecting, Modeling, and Predicting User Temporal Intention , Hany M. SalahEldeen

Dissertation: Wireless Networking for Vehicle to Infrastructure Communication and Automatic Incident Detection , Sarwar Aziz Sha-Mohammad

Dissertation: Computational Development for Secondary Structure Detection From Three-Dimensional Images of Cryo-Electron Microscopy , Dong Si

Thesis: Mobile Cloud Computing Based Non Rigid Registration for Image Guided Surgery , Arun Brahmavar Vishwanatha

Theses/Dissertations from 2014 2014

Dissertation: Web Archive Services Framework for Tighter Integration Between the Past and Present Web , Ahmed AlSum

Dissertation: Modeling Stem Cell Population Dynamics , Samiur Arif

Dissertation: A Framework for Web Object Self-Preservation , Charles L. Cartledge

Dissertation: Document Classification in Support of Automated Metadata Extraction Form Heterogeneous Collections , Paul K. Flynn

Dissertation: Resource Allocation in Vehicular Cloud Computing , Puya Ghazizadeh

Thesis: Generating Combinatorial Objects- A New Perspective , Alexander Chizoma Nwala

Dissertation: Enhancing Understanding of Discrete Event Simulation Models Through Analysis , Kara Ann Olson

Dissertation: Scalable Reasoning for Knowledge Bases Subject to Changes , Hui Shi

Dissertation: Improving Structural Features Prediction in Protein Structure Modeling , Ashraf Yaseen

Thesis: Computational Analysis of Gene Expression and Connectivity Patterns in the Convoluted Structures of Mouse Cerebellum , Tao Zeng

Theses/Dissertations from 2013 2013

Thesis: HTTP Mailbox - Asynchronous Restful Communication , Sawood Alam

Dissertation: TDMA Slot Reservation in Cluster-Based VANETs , Mohammad Salem Almalag

Thesis: Protein Loop Length Estimation From Medium Resolution Cryoem Images , Andrew R. McKnight

Theses/Dissertations from 2012 2012

Dissertation: De Novo Protein Structure Modeling from Cryoem Data Through a Dynamic Programming Algorithm in the Secondary Structure Topology Graph , Kamal H. Al Nasr

Dissertation: FRIEND: A Cyber-Physical System for Traffic Flow Related Information Aggregation and Dissemination , Samy S. El-Tawab

Thesis: An Extensible Framework for Creating Personal Archives of Web Resources Requiring Authentication , Matthew Ryan Kelly

Thesis: Visualizing Digital Collections at Archive-It , Kalpesh Padia

Theses/Dissertations from 2011 2011

Dissertation: A Framework for Incident Detection and notification in Vehicular Ad-Hoc Networks , Mahmoud Abuelela

Dissertation: A Framework for Dynamic Traffic Monitoring Using Vehicular Ad-Hoc Networks , Mohammad Hadi Arbabi

Thesis: A Probabilistic Analysis of Misparking in Reservation Based Parking Garages , Vikas G. Ashok

Thesis: A Penalty-Based Approach to Handling Cluster Sizing in Mobile Ad Hoc Networks , Ryan Florin

Dissertation: Data Aggregation and Dissemination in Vehicular Ad-Hoc Networks , Khaled Ibrahim

Dissertation: Using the Web Infrastructure for Real Time Recovery of Missing Web Pages , Martin Klein

Theses/Dissertations from 2010 2010

Dissertation: A Virtual Infrastructure for Mitigating Typical Challenges in Sensor Networks , Hady S. Abdel Salam

Thesis: Merging Schemas in a Collaborative Faceted Classification System , Jianxiang Li

Thesis: XPath-Based Template Language for Describing the Placement of Metadata within a Document , Vijay Kumar Musham

Dissertation: Providing Location Security in Vehicular Ad Hoc Networks , Gongjun Yan

Theses/Dissertations from 2009 2009

Dissertation: Algorithms for Vertex-Weighted Matching in Graphs , Mahantesh Halappanavar

Theses/Dissertations from 2008 2008

Thesis: Using Timed-Release Cryptography to Mitigate Preservation Risk of Embargo Periods , Rabia Haq

Dissertation: Biology-Inspired Approach for Communal Behavior in Massively Deployed Sensor Networks , Kennie H. Jones

Dissertation: Biological Networks: Modeling and Structural Analysis , Emad Y. Ramadan

Dissertation: Integrating Preservation Functions Into the Web Server , Joan A. Smith

Theses/Dissertations from 2007 2007

Dissertation: FreeLib: A Self-Sustainable Peer-to-Peer Digital Library Framework for Evolving Communities , Ashraf A. Amrou

Thesis: Channel Management in Heterogeneous Cellular Networks , Mohammad Hadi Arbabi

Dissertation: Diagnosing Reading strategies: Paraphrase Recognition , Chutima Boonthum

Thesis: Investigating Real-Time Sonar Performance Predictions Using Beowulf Clustering , Charles Lane Cartledge

Dissertation: Lazy Preservation: Reconstructing Websites from the Web Infrastructure , Frank McCown

Theses/Dissertations from 2006 2006

Dissertation: Group Key Management in Wireless Ad-Hoc and Sensor Networks , Mohammed A. Moharrum

Dissertation: Template-Based Metadata Extraction for Heterogeneous Collection , Jianfeng Tang

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Computer Science Thesis Topics

This page provides a comprehensive list of computer science thesis topics , carefully curated to support students in identifying and selecting innovative and relevant areas for their academic research. Whether you are at the beginning of your research journey or are seeking a specific area to explore further, this guide aims to serve as an essential resource. With an expansive array of topics spread across various sub-disciplines of computer science, this list is designed to meet a diverse range of interests and academic needs. From the complexities of artificial intelligence to the intricate designs of web development, each category is equipped with 40 specific topics, offering a breadth of possibilities to inspire your next big thesis project. Explore our guide to find not only a topic that resonates with your academic ambitions but also one that has the potential to contribute significantly to the field of computer science.

1000 Computer Science Thesis Topics and Ideas

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Get 10% off with 24start discount code, browse computer science thesis topics:, artificial intelligence thesis topics, augmented reality thesis topics, big data analytics thesis topics, bioinformatics thesis topics, blockchain technology thesis topics, cloud computing thesis topics, computer engineering thesis topics, computer vision thesis topics, cybersecurity thesis topics, data science thesis topics, digital transformation thesis topics, distributed systems and networks thesis topics, geographic information systems (gis) thesis topics, human-computer interaction (hci) thesis topics, image processing thesis topics, information system thesis topics, information technology thesis topics.

Internet Of Things (IoT) Thesis Topics

Machine Learning Thesis Topics

Neural networks thesis topics, programming thesis topics, quantum computing thesis topics, robotics thesis topics, software engineering thesis topics, web development thesis topics.

Ethical Implications of AI in Decision-Making Processes
The Role of AI in Personalized Medicine: Opportunities and Challenges
Advances in AI-Driven Predictive Analytics in Retail
AI in Autonomous Vehicles: Safety, Regulation, and Technology Integration
Natural Language Processing: Improving Human-Machine Interaction
The Future of AI in Cybersecurity: Threats and Defenses
Machine Learning Algorithms for Real-Time Data Processing
AI and the Internet of Things: Transforming Smart Home Technology
The Impact of Deep Learning on Image Recognition Technologies
Reinforcement Learning: Applications in Robotics and Automation
AI in Finance: Algorithmic Trading and Risk Assessment
Bias and Fairness in AI: Addressing Socio-Technical Challenges
The Evolution of AI in Education: Customized Learning Experiences
AI for Environmental Conservation: Tracking and Predictive Analysis
The Role of Artificial Neural Networks in Weather Forecasting
AI in Agriculture: Predictive Analytics for Crop and Soil Management
Emotional Recognition AI: Implications for Mental Health Assessments
AI in Space Exploration: Autonomous Rovers and Mission Planning
Enhancing User Experience with AI in Video Games
AI-Powered Virtual Assistants: Trends, Effectiveness, and User Trust
The Integration of AI in Traditional Industries: Case Studies
Generative AI Models in Art and Creativity
AI in LegalTech: Document Analysis and Litigation Prediction
Healthcare Diagnostics: AI Applications in Radiology and Pathology
AI and Blockchain: Enhancing Security in Decentralized Systems
Ethics of AI in Surveillance: Privacy vs. Security
AI in E-commerce: Personalization Engines and Customer Behavior Analysis
The Future of AI in Telecommunications: Network Optimization and Service Delivery
AI in Manufacturing: Predictive Maintenance and Quality Control
Challenges of AI in Elderly Care: Ethical Considerations and Technological Solutions
The Role of AI in Public Safety and Emergency Response
AI for Content Creation: Impact on Media and Journalism
AI-Driven Algorithms for Efficient Energy Management
The Role of AI in Cultural Heritage Preservation
AI and the Future of Public Transport: Optimization and Management
Enhancing Sports Performance with AI-Based Analytics
AI in Human Resources: Automating Recruitment and Employee Management
Real-Time Translation AI: Breaking Language Barriers
AI in Mental Health: Tools for Monitoring and Therapy Assistance
The Future of AI Governance: Regulation and Standardization
AR in Medical Training and Surgery Simulation
The Impact of Augmented Reality in Retail: Enhancing Consumer Experience
Augmented Reality for Enhanced Navigation Systems
AR Applications in Maintenance and Repair in Industrial Settings
The Role of AR in Enhancing Online Education
Augmented Reality in Cultural Heritage: Interactive Visitor Experiences
Developing AR Tools for Improved Sports Coaching and Training
Privacy and Security Challenges in Augmented Reality Applications
The Future of AR in Advertising: Engagement and Measurement
User Interface Design for AR: Principles and Best Practices
AR in Automotive Industry: Enhancing Driving Experience and Safety
Augmented Reality for Emergency Response Training
AR and IoT: Converging Technologies for Smart Environments
Enhancing Physical Rehabilitation with AR Applications
The Role of AR in Enhancing Public Safety and Awareness
Augmented Reality in Fashion: Virtual Fitting and Personalized Shopping
AR for Environmental Education: Interactive and Immersive Learning
The Use of AR in Building and Architecture Planning
AR in the Entertainment Industry: Games and Live Events
Implementing AR in Museums and Art Galleries for Interactive Learning
Augmented Reality for Real Estate: Virtual Tours and Property Visualization
AR in Consumer Electronics: Integration in Smart Devices
The Development of AR Applications for Children’s Education
AR for Enhancing User Engagement in Social Media Platforms
The Application of AR in Field Service Management
Augmented Reality for Disaster Management and Risk Assessment
Challenges of Content Creation for Augmented Reality
Future Trends in AR Hardware: Wearables and Beyond
Legal and Ethical Considerations of Augmented Reality Technology
AR in Space Exploration: Tools for Simulation and Training
Interactive Shopping Experiences with AR: The Future of Retail
AR in Wildlife Conservation: Educational Tools and Awareness
The Impact of AR on the Publishing Industry: Interactive Books and Magazines
Augmented Reality and Its Role in Automotive Manufacturing
AR for Job Training: Bridging the Skill Gap in Various Industries
The Role of AR in Therapy: New Frontiers in Mental Health Treatment
The Future of Augmented Reality in Sports Broadcasting
AR as a Tool for Enhancing Public Art Installations
Augmented Reality in the Tourism Industry: Personalized Travel Experiences
The Use of AR in Security Training: Realistic and Safe Simulations
The Role of Big Data in Improving Healthcare Outcomes
Big Data and Its Impact on Consumer Behavior Analysis
Privacy Concerns in Big Data: Ethical and Legal Implications
The Application of Big Data in Predictive Maintenance for Manufacturing
Real-Time Big Data Processing: Tools and Techniques
Big Data in Financial Services: Fraud Detection and Risk Management
The Evolution of Big Data Technologies: From Hadoop to Spark
Big Data Visualization: Techniques for Effective Communication of Insights
The Integration of Big Data and Artificial Intelligence
Big Data in Smart Cities: Applications in Traffic Management and Energy Use
Enhancing Supply Chain Efficiency with Big Data Analytics
Big Data in Sports Analytics: Improving Team Performance and Fan Engagement
The Role of Big Data in Environmental Monitoring and Sustainability
Big Data and Social Media: Analyzing Sentiments and Trends
Scalability Challenges in Big Data Systems
The Future of Big Data in Retail: Personalization and Customer Experience
Big Data in Education: Customized Learning Paths and Student Performance Analysis
Privacy-Preserving Techniques in Big Data
Big Data in Public Health: Epidemiology and Disease Surveillance
The Impact of Big Data on Insurance: Tailored Policies and Pricing
Edge Computing in Big Data: Processing at the Source
Big Data and the Internet of Things: Generating Insights from IoT Data
Cloud-Based Big Data Analytics: Opportunities and Challenges
Big Data Governance: Policies, Standards, and Management
The Role of Big Data in Crisis Management and Response
Machine Learning with Big Data: Building Predictive Models
Big Data in Agriculture: Precision Farming and Yield Optimization
The Ethics of Big Data in Research: Consent and Anonymity
Cross-Domain Big Data Integration: Challenges and Solutions
Big Data and Cybersecurity: Threat Detection and Prevention Strategies
Real-Time Streaming Analytics in Big Data
Big Data in the Media Industry: Content Optimization and Viewer Insights
The Impact of GDPR on Big Data Practices
Quantum Computing and Big Data: Future Prospects
Big Data in E-Commerce: Optimizing Logistics and Inventory Management
Big Data Talent: Education and Skill Development for Data Scientists
The Role of Big Data in Political Campaigns and Voting Behavior Analysis
Big Data and Mental Health: Analyzing Patterns for Better Interventions
Big Data in Genomics and Personalized Medicine
The Future of Big Data in Autonomous Driving Technologies
The Role of Bioinformatics in Personalized Medicine
Next-Generation Sequencing Data Analysis: Challenges and Opportunities
Bioinformatics and the Study of Genetic Diseases
Computational Models for Understanding Protein Structure and Function
Bioinformatics in Drug Discovery and Development
The Impact of Big Data on Bioinformatics: Data Management and Analysis
Machine Learning Applications in Bioinformatics
Bioinformatics Approaches for Cancer Genomics
The Development of Bioinformatics Tools for Metagenomics Analysis
Ethical Considerations in Bioinformatics: Data Sharing and Privacy
The Role of Bioinformatics in Agricultural Biotechnology
Bioinformatics and Viral Evolution: Tracking Pathogens and Outbreaks
The Integration of Bioinformatics and Systems Biology
Bioinformatics in Neuroscience: Mapping the Brain
The Future of Bioinformatics in Non-Invasive Prenatal Testing
Bioinformatics and the Human Microbiome: Health Implications
The Application of Artificial Intelligence in Bioinformatics
Structural Bioinformatics: Computational Techniques for Molecular Modeling
Comparative Genomics: Insights into Evolution and Function
Bioinformatics in Immunology: Vaccine Design and Immune Response Analysis
High-Performance Computing in Bioinformatics
The Challenge of Proteomics in Bioinformatics
RNA-Seq Data Analysis and Interpretation
Cloud Computing Solutions for Bioinformatics Data
Computational Epigenetics: DNA Methylation and Histone Modification Analysis
Bioinformatics in Ecology: Biodiversity and Conservation Genetics
The Role of Bioinformatics in Forensic Analysis
Mobile Apps and Tools for Bioinformatics Research
Bioinformatics and Public Health: Epidemiological Studies
The Use of Bioinformatics in Clinical Diagnostics
Genetic Algorithms in Bioinformatics
Bioinformatics for Aging Research: Understanding the Mechanisms of Aging
Data Visualization Techniques in Bioinformatics
Bioinformatics and the Development of Therapeutic Antibodies
The Role of Bioinformatics in Stem Cell Research
Bioinformatics and Cardiovascular Diseases: Genomic Insights
The Impact of Machine Learning on Functional Genomics in Bioinformatics
Bioinformatics in Dental Research: Genetic Links to Oral Diseases
The Future of CRISPR Technology and Bioinformatics
Bioinformatics and Nutrition: Genomic Insights into Diet and Health
Blockchain for Enhancing Cybersecurity in Various Industries
The Impact of Blockchain on Supply Chain Transparency
Blockchain in Healthcare: Patient Data Management and Security
The Application of Blockchain in Voting Systems
Blockchain and Smart Contracts: Legal Implications and Applications
Cryptocurrencies: Market Trends and the Future of Digital Finance
Blockchain in Real Estate: Improving Property and Land Registration
The Role of Blockchain in Managing Digital Identities
Blockchain for Intellectual Property Management
Energy Sector Innovations: Blockchain for Renewable Energy Distribution
Blockchain and the Future of Public Sector Operations
The Impact of Blockchain on Cross-Border Payments
Blockchain for Non-Fungible Tokens (NFTs): Applications in Art and Media
Privacy Issues in Blockchain Applications
Blockchain in the Automotive Industry: Supply Chain and Beyond
Decentralized Finance (DeFi): Opportunities and Challenges
The Role of Blockchain in Combating Counterfeiting and Fraud
Blockchain for Sustainable Environmental Practices
The Integration of Artificial Intelligence with Blockchain
Blockchain Education: Curriculum Development and Training Needs
Blockchain in the Music Industry: Rights Management and Revenue Distribution
The Challenges of Blockchain Scalability and Performance Optimization
The Future of Blockchain in the Telecommunications Industry
Blockchain and Consumer Data Privacy: A New Paradigm
Blockchain for Disaster Recovery and Business Continuity
Blockchain in the Charity and Non-Profit Sectors
Quantum Resistance in Blockchain: Preparing for the Quantum Era
Blockchain and Its Impact on Traditional Banking and Financial Institutions
Legal and Regulatory Challenges Facing Blockchain Technology
Blockchain for Improved Logistics and Freight Management
The Role of Blockchain in the Evolution of the Internet of Things (IoT)
Blockchain and the Future of Gaming: Transparency and Fair Play
Blockchain for Academic Credentials Verification
The Application of Blockchain in the Insurance Industry
Blockchain and the Future of Content Creation and Distribution
Blockchain for Enhancing Data Integrity in Scientific Research
The Impact of Blockchain on Human Resources: Employee Verification and Salary Payments
Blockchain and the Future of Retail: Customer Loyalty Programs and Inventory Management
Blockchain and Industrial Automation: Trust and Efficiency
Blockchain for Digital Marketing: Transparency and Consumer Engagement
Multi-Cloud Strategies: Optimization and Security Challenges
Advances in Cloud Computing Architectures for Scalable Applications
Edge Computing: Extending the Reach of Cloud Services
Cloud Security: Novel Approaches to Data Encryption and Threat Mitigation
The Impact of Serverless Computing on Software Development Lifecycle
Cloud Computing and Sustainability: Energy-Efficient Data Centers
Cloud Service Models: Comparative Analysis of IaaS, PaaS, and SaaS
Cloud Migration Strategies: Best Practices and Common Pitfalls
The Role of Cloud Computing in Big Data Analytics
Implementing AI and Machine Learning Workloads on Cloud Platforms
Hybrid Cloud Environments: Management Tools and Techniques
Cloud Computing in Healthcare: Compliance, Security, and Use Cases
Cost-Effective Cloud Solutions for Small and Medium Enterprises (SMEs)
The Evolution of Cloud Storage Solutions: Trends and Technologies
Cloud-Based Disaster Recovery Solutions: Design and Reliability
Blockchain in Cloud Services: Enhancing Transparency and Trust
Cloud Networking: Managing Connectivity and Traffic in Cloud Environments
Cloud Governance: Managing Compliance and Operational Risks
The Future of Cloud Computing: Quantum Computing Integration
Performance Benchmarking of Cloud Services Across Different Providers
Privacy Preservation in Cloud Environments
Cloud Computing in Education: Virtual Classrooms and Learning Management Systems
Automation in Cloud Deployments: Tools and Strategies
Cloud Auditing and Monitoring Techniques
Mobile Cloud Computing: Challenges and Future Trends
The Role of Cloud Computing in Digital Media Production and Distribution
Security Risks in Multi-Tenancy Cloud Environments
Cloud Computing for Scientific Research: Enabling Complex Simulations
The Impact of 5G on Cloud Computing Services
Federated Clouds: Building Collaborative Cloud Environments
Managing Software Dependencies in Cloud Applications
The Economics of Cloud Computing: Cost Models and Pricing Strategies
Cloud Computing in Government: Security Protocols and Citizen Services
Cloud Access Security Brokers (CASBs): Security Enforcement Points
DevOps in the Cloud: Strategies for Continuous Integration and Deployment
Predictive Analytics in Cloud Computing
The Role of Cloud Computing in IoT Deployment
Implementing Robust Cybersecurity Measures in Cloud Architecture
Cloud Computing in the Financial Sector: Handling Sensitive Data
Future Trends in Cloud Computing: The Role of AI in Cloud Optimization
Advances in Microprocessor Design and Architecture
FPGA-Based Design: Innovations and Applications
The Role of Embedded Systems in Consumer Electronics
Quantum Computing: Hardware Development and Challenges
High-Performance Computing (HPC) and Parallel Processing
Design and Analysis of Computer Networks
Cyber-Physical Systems: Design, Analysis, and Security
The Impact of Nanotechnology on Computer Hardware
Wireless Sensor Networks: Design and Optimization
Cryptographic Hardware: Implementations and Security Evaluations
Machine Learning Techniques for Hardware Optimization
Hardware for Artificial Intelligence: GPUs vs. TPUs
Energy-Efficient Hardware Designs for Sustainable Computing
Security Aspects of Mobile and Ubiquitous Computing
Advanced Algorithms for Computer-Aided Design (CAD) of VLSI
Signal Processing in Communication Systems
The Development of Wearable Computing Devices
Computer Hardware Testing: Techniques and Tools
The Role of Hardware in Network Security
The Evolution of Interface Designs in Consumer Electronics
Biometric Systems: Hardware and Software Integration
The Integration of IoT Devices in Smart Environments
Electronic Design Automation (EDA) Tools and Methodologies
Robotics: Hardware Design and Control Systems
Hardware Accelerators for Deep Learning Applications
Developments in Non-Volatile Memory Technologies
The Future of Computer Hardware in the Era of Quantum Computing
Hardware Solutions for Data Storage and Retrieval
Power Management Techniques in Embedded Systems
Challenges in Designing Multi-Core Processors
System on Chip (SoC) Design Trends and Challenges
The Role of Computer Engineering in Aerospace Technology
Real-Time Systems: Design and Implementation Challenges
Hardware Support for Virtualization Technology
Advances in Computer Graphics Hardware
The Impact of 5G Technology on Mobile Computing Hardware
Environmental Impact Assessment of Computer Hardware Production
Security Vulnerabilities in Modern Microprocessors
Computer Hardware Innovations in the Automotive Industry
The Role of Computer Engineering in Medical Device Technology
Deep Learning Approaches to Object Recognition
Real-Time Image Processing for Autonomous Vehicles
Computer Vision in Robotic Surgery: Techniques and Challenges
Facial Recognition Technology: Innovations and Privacy Concerns
Machine Vision in Industrial Automation and Quality Control
3D Reconstruction Techniques in Computer Vision
Enhancing Sports Analytics with Computer Vision
Augmented Reality: Integrating Computer Vision for Immersive Experiences
Computer Vision for Environmental Monitoring
Thermal Imaging and Its Applications in Computer Vision
Computer Vision in Retail: Customer Behavior and Store Layout Optimization
Motion Detection and Tracking in Security Systems
The Role of Computer Vision in Content Moderation on Social Media
Gesture Recognition: Methods and Applications
Computer Vision in Agriculture: Pest Detection and Crop Analysis
Advances in Medical Imaging: Machine Learning and Computer Vision
Scene Understanding and Contextual Inference in Images
The Development of Vision-Based Autonomous Drones
Optical Character Recognition (OCR): Latest Techniques and Applications
The Impact of Computer Vision on Virtual Reality Experiences
Biometrics: Enhancing Security Systems with Computer Vision
Computer Vision for Wildlife Conservation: Species Recognition and Behavior Analysis
Underwater Image Processing: Challenges and Techniques
Video Surveillance: The Evolution of Algorithmic Approaches
Advanced Driver-Assistance Systems (ADAS): Leveraging Computer Vision
Computational Photography: Enhancing Image Capture Techniques
The Integration of AI in Computer Vision: Ethical and Technical Considerations
Computer Vision in the Gaming Industry: From Design to Interaction
The Future of Computer Vision in Smart Cities
Pattern Recognition in Historical Document Analysis
The Role of Computer Vision in the Manufacturing of Customized Products
Enhancing Accessibility with Computer Vision: Tools for the Visually Impaired
The Use of Computer Vision in Behavioral Research
Predictive Analytics with Computer Vision in Sports
Image Synthesis with Generative Adversarial Networks (GANs)
The Use of Computer Vision in Remote Sensing
Real-Time Video Analytics for Public Safety
The Role of Computer Vision in Telemedicine
Computer Vision and the Internet of Things (IoT): A Synergistic Approach
Future Trends in Computer Vision: Quantum Computing and Beyond
Advances in Cryptography: Post-Quantum Cryptosystems
Artificial Intelligence in Cybersecurity: Threat Detection and Response
Blockchain for Enhanced Security in Distributed Networks
The Impact of IoT on Cybersecurity: Vulnerabilities and Solutions
Cybersecurity in Cloud Computing: Best Practices and Tools
Ethical Hacking: Techniques and Ethical Implications
The Role of Human Factors in Cybersecurity Breaches
Privacy-preserving Technologies in an Age of Surveillance
The Evolution of Ransomware Attacks and Defense Strategies
Secure Software Development: Integrating Security in DevOps (DevSecOps)
Cybersecurity in Critical Infrastructure: Challenges and Innovations
The Future of Biometric Security Systems
Cyber Warfare: State-sponsored Attacks and Defense Mechanisms
The Role of Cybersecurity in Protecting Digital Identities
Social Engineering Attacks: Prevention and Countermeasures
Mobile Security: Protecting Against Malware and Exploits
Wireless Network Security: Protocols and Practices
Data Breaches: Analysis, Consequences, and Mitigation
The Ethics of Cybersecurity: Balancing Privacy and Security
Regulatory Compliance and Cybersecurity: GDPR and Beyond
The Impact of 5G Technology on Cybersecurity
The Role of Machine Learning in Cyber Threat Intelligence
Cybersecurity in Automotive Systems: Challenges in a Connected Environment
The Use of Virtual Reality for Cybersecurity Training and Simulation
Advanced Persistent Threats (APT): Detection and Response
Cybersecurity for Smart Cities: Challenges and Solutions
Deep Learning Applications in Malware Detection
The Role of Cybersecurity in Healthcare: Protecting Patient Data
Supply Chain Cybersecurity: Identifying Risks and Solutions
Endpoint Security: Trends, Challenges, and Future Directions
Forensic Techniques in Cybersecurity: Tracking and Analyzing Cyber Crimes
The Influence of International Law on Cyber Operations
Protecting Financial Institutions from Cyber Frauds and Attacks
Quantum Computing and Its Implications for Cybersecurity
Cybersecurity and Remote Work: Emerging Threats and Strategies
IoT Security in Industrial Applications
Cyber Insurance: Risk Assessment and Management
Security Challenges in Edge Computing Environments
Anomaly Detection in Network Security Using AI Techniques
Securing the Software Supply Chain in Application Development
Big Data Analytics: Techniques and Applications in Real-time
Machine Learning Algorithms for Predictive Analytics
Data Science in Healthcare: Improving Patient Outcomes with Predictive Models
The Role of Data Science in Financial Market Predictions
Natural Language Processing: Emerging Trends and Applications
Data Visualization Tools and Techniques for Enhanced Business Intelligence
Ethics in Data Science: Privacy, Fairness, and Transparency
The Use of Data Science in Environmental Science for Sustainability Studies
The Impact of Data Science on Social Media Marketing Strategies
Data Mining Techniques for Detecting Patterns in Large Datasets
AI and Data Science: Synergies and Future Prospects
Reinforcement Learning: Applications and Challenges in Data Science
The Role of Data Science in E-commerce Personalization
Predictive Maintenance in Manufacturing Through Data Science
The Evolution of Recommendation Systems in Streaming Services
Real-time Data Processing with Stream Analytics
Deep Learning for Image and Video Analysis
Data Governance in Big Data Analytics
Text Analytics and Sentiment Analysis for Customer Feedback
Fraud Detection in Banking and Insurance Using Data Science
The Integration of IoT Data in Data Science Models
The Future of Data Science in Quantum Computing
Data Science for Public Health: Epidemic Outbreak Prediction
Sports Analytics: Performance Improvement and Injury Prevention
Data Science in Retail: Inventory Management and Customer Journey Analysis
Data Science in Smart Cities: Traffic and Urban Planning
The Use of Blockchain in Data Security and Integrity
Geospatial Analysis for Environmental Monitoring
Time Series Analysis in Economic Forecasting
Data Science in Education: Analyzing Trends and Student Performance
Predictive Policing: Data Science in Law Enforcement
Data Science in Agriculture: Yield Prediction and Soil Health
Computational Social Science: Analyzing Societal Trends
Data Science in Energy Sector: Consumption and Optimization
Personalization Technologies in Healthcare Through Data Science
The Role of Data Science in Content Creation and Media
Anomaly Detection in Network Security Using Data Science Techniques
The Future of Autonomous Vehicles: Data Science-Driven Innovations
Multimodal Data Fusion Techniques in Data Science
Scalability Challenges in Data Science Projects
The Role of Digital Transformation in Business Model Innovation
The Impact of Digital Technologies on Customer Experience
Digital Transformation in the Banking Sector: Trends and Challenges
The Use of AI and Robotics in Digital Transformation of Manufacturing
Digital Transformation in Healthcare: Telemedicine and Beyond
The Influence of Big Data on Decision-Making Processes in Corporations
Blockchain as a Driver for Transparency in Digital Transformation
The Role of IoT in Enhancing Operational Efficiency in Industries
Digital Marketing Strategies: SEO, Content, and Social Media
The Integration of Cyber-Physical Systems in Industrial Automation
Digital Transformation in Education: Virtual Learning Environments
Smart Cities: The Role of Digital Technologies in Urban Planning
Digital Transformation in the Retail Sector: E-commerce Evolution
The Future of Work: Impact of Digital Transformation on Workplaces
Cybersecurity Challenges in a Digitally Transformed World
Mobile Technologies and Their Impact on Digital Transformation
The Role of Digital Twin Technology in Industry 4.0
Digital Transformation in the Public Sector: E-Government Services
Data Privacy and Security in the Age of Digital Transformation
Digital Transformation in the Energy Sector: Smart Grids and Renewable Energy
The Use of Augmented Reality in Training and Development
The Role of Virtual Reality in Real Estate and Architecture
Digital Transformation and Sustainability: Reducing Environmental Footprint
The Role of Digital Transformation in Supply Chain Optimization
Digital Transformation in Agriculture: IoT and Smart Farming
The Impact of 5G on Digital Transformation Initiatives
The Influence of Digital Transformation on Media and Entertainment
Digital Transformation in Insurance: Telematics and Risk Assessment
The Role of AI in Enhancing Customer Service Operations
The Future of Digital Transformation: Trends and Predictions
Digital Transformation and Corporate Governance
The Role of Leadership in Driving Digital Transformation
Digital Transformation in Non-Profit Organizations: Challenges and Benefits
The Economic Implications of Digital Transformation
The Cultural Impact of Digital Transformation on Organizations
Digital Transformation in Transportation: Logistics and Fleet Management
User Experience (UX) Design in Digital Transformation
The Role of Digital Transformation in Crisis Management
Digital Transformation and Human Resource Management
Implementing Change Management in Digital Transformation Projects
Scalability Challenges in Distributed Systems: Solutions and Strategies
Blockchain Technology: Enhancing Security and Transparency in Distributed Networks
The Role of Edge Computing in Distributed Systems
Designing Fault-Tolerant Systems in Distributed Networks
The Impact of 5G Technology on Distributed Network Architectures
Machine Learning Algorithms for Network Traffic Analysis
Load Balancing Techniques in Distributed Computing
The Use of Distributed Ledger Technology Beyond Cryptocurrencies
Network Function Virtualization (NFV) and Its Impact on Service Providers
The Evolution of Software-Defined Networking (SDN) in Enterprise Environments
Implementing Robust Cybersecurity Measures in Distributed Systems
Quantum Computing: Implications for Network Security in Distributed Systems
Peer-to-Peer Network Protocols and Their Applications
The Internet of Things (IoT): Network Challenges and Communication Protocols
Real-Time Data Processing in Distributed Sensor Networks
The Role of Artificial Intelligence in Optimizing Network Operations
Privacy and Data Protection Strategies in Distributed Systems
The Future of Distributed Computing in Cloud Environments
Energy Efficiency in Distributed Network Systems
Wireless Mesh Networks: Design, Challenges, and Applications
Multi-Access Edge Computing (MEC): Use Cases and Deployment Challenges
Consensus Algorithms in Distributed Systems: From Blockchain to New Applications
The Use of Containers and Microservices in Building Scalable Applications
Network Slicing for 5G: Opportunities and Challenges
The Role of Distributed Systems in Big Data Analytics
Managing Data Consistency in Distributed Databases
The Impact of Distributed Systems on Digital Transformation Strategies
Augmented Reality over Distributed Networks: Performance and Scalability Issues
The Application of Distributed Systems in Smart Grid Technology
Developing Distributed Applications Using Serverless Architectures
The Challenges of Implementing IPv6 in Distributed Networks
Distributed Systems for Disaster Recovery: Design and Implementation
The Use of Virtual Reality in Distributed Network Environments
Security Protocols for Ad Hoc Networks in Emergency Situations
The Role of Distributed Networks in Enhancing Mobile Broadband Services
Next-Generation Protocols for Enhanced Network Reliability and Performance
The Application of Blockchain in Securing Distributed IoT Networks
Dynamic Resource Allocation Strategies in Distributed Systems
The Integration of Distributed Systems with Existing IT Infrastructure
The Future of Autonomous Systems in Distributed Networking
The Integration of GIS with Remote Sensing for Environmental Monitoring
GIS in Urban Planning: Techniques for Sustainable Development
The Role of GIS in Disaster Management and Response Strategies
Real-Time GIS Applications in Traffic Management and Route Planning
The Use of GIS in Water Resource Management
GIS and Public Health: Tracking Epidemics and Healthcare Access
Advances in 3D GIS: Technologies and Applications
GIS in Agricultural Management: Precision Farming Techniques
The Impact of GIS on Biodiversity Conservation Efforts
Spatial Data Analysis for Crime Pattern Detection and Prevention
GIS in Renewable Energy: Site Selection and Resource Management
The Role of GIS in Historical Research and Archaeology
GIS and Machine Learning: Integrating Spatial Analysis with Predictive Models
Cloud Computing and GIS: Enhancing Accessibility and Data Processing
The Application of GIS in Managing Public Transportation Systems
GIS in Real Estate: Market Analysis and Property Valuation
The Use of GIS for Environmental Impact Assessments
Mobile GIS Applications: Development and Usage Trends
GIS and Its Role in Smart City Initiatives
Privacy Issues in the Use of Geographic Information Systems
GIS in Forest Management: Monitoring and Conservation Strategies
The Impact of GIS on Tourism: Enhancing Visitor Experiences through Technology
GIS in the Insurance Industry: Risk Assessment and Policy Design
The Development of Participatory GIS (PGIS) for Community Engagement
GIS in Coastal Management: Addressing Erosion and Flood Risks
Geospatial Analytics in Retail: Optimizing Location and Consumer Insights
GIS for Wildlife Tracking and Habitat Analysis
The Use of GIS in Climate Change Studies
GIS and Social Media: Analyzing Spatial Trends from User Data
The Future of GIS: Augmented Reality and Virtual Reality Applications
GIS in Education: Tools for Teaching Geographic Concepts
The Role of GIS in Land Use Planning and Zoning
GIS for Emergency Medical Services: Optimizing Response Times
Open Source GIS Software: Development and Community Contributions
GIS and the Internet of Things (IoT): Converging Technologies for Advanced Monitoring
GIS for Mineral Exploration: Techniques and Applications
The Role of GIS in Municipal Management and Services
GIS and Drone Technology: A Synergy for Precision Mapping
Spatial Statistics in GIS: Techniques for Advanced Data Analysis
Future Trends in GIS: The Integration of AI for Smarter Solutions
The Evolution of User Interface (UI) Design: From Desktop to Mobile and Beyond
The Role of HCI in Enhancing Accessibility for Disabled Users
Virtual Reality (VR) and Augmented Reality (AR) in HCI: New Dimensions of Interaction
The Impact of HCI on User Experience (UX) in Software Applications
Cognitive Aspects of HCI: Understanding User Perception and Behavior
HCI and the Internet of Things (IoT): Designing Interactive Smart Devices
The Use of Biometrics in HCI: Security and Usability Concerns
HCI in Educational Technologies: Enhancing Learning through Interaction
Emotional Recognition and Its Application in HCI
The Role of HCI in Wearable Technology: Design and Functionality
Advanced Techniques in Voice User Interfaces (VUIs)
The Impact of HCI on Social Media Interaction Patterns
HCI in Healthcare: Designing User-Friendly Medical Devices and Software
HCI and Gaming: Enhancing Player Engagement and Experience
The Use of HCI in Robotic Systems: Improving Human-Robot Interaction
The Influence of HCI on E-commerce: Optimizing User Journeys and Conversions
HCI in Smart Homes: Interaction Design for Automated Environments
Multimodal Interaction: Integrating Touch, Voice, and Gesture in HCI
HCI and Aging: Designing Technology for Older Adults
The Role of HCI in Virtual Teams: Tools and Strategies for Collaboration
User-Centered Design: HCI Strategies for Developing User-Focused Software
HCI Research Methodologies: Experimental Design and User Studies
The Application of HCI Principles in the Design of Public Kiosks
The Future of HCI: Integrating Artificial Intelligence for Smarter Interfaces
HCI in Transportation: Designing User Interfaces for Autonomous Vehicles
Privacy and Ethics in HCI: Addressing User Data Security
HCI and Environmental Sustainability: Promoting Eco-Friendly Behaviors
Adaptive Interfaces: HCI Design for Personalized User Experiences
The Role of HCI in Content Creation: Tools for Artists and Designers
HCI for Crisis Management: Designing Systems for Emergency Use
The Use of HCI in Sports Technology: Enhancing Training and Performance
The Evolution of Haptic Feedback in HCI
HCI and Cultural Differences: Designing for Global User Bases
The Impact of HCI on Digital Marketing: Creating Engaging User Interactions
HCI in Financial Services: Improving User Interfaces for Banking Apps
The Role of HCI in Enhancing User Trust in Technology
HCI for Public Safety: User Interfaces for Security Systems
The Application of HCI in the Film and Television Industry
HCI and the Future of Work: Designing Interfaces for Remote Collaboration
Innovations in HCI: Exploring New Interaction Technologies and Their Applications
Deep Learning Techniques for Advanced Image Segmentation
Real-Time Image Processing for Autonomous Driving Systems
Image Enhancement Algorithms for Underwater Imaging
Super-Resolution Imaging: Techniques and Applications
The Role of Image Processing in Remote Sensing and Satellite Imagery Analysis
Machine Learning Models for Medical Image Diagnosis
The Impact of AI on Photographic Restoration and Enhancement
Image Processing in Security Systems: Facial Recognition and Motion Detection
Advanced Algorithms for Image Noise Reduction
3D Image Reconstruction Techniques in Tomography
Image Processing for Agricultural Monitoring: Crop Disease Detection and Yield Prediction
Techniques for Panoramic Image Stitching
Video Image Processing: Real-Time Streaming and Data Compression
The Application of Image Processing in Printing Technology
Color Image Processing: Theory and Practical Applications
The Use of Image Processing in Biometrics Identification
Computational Photography: Image Processing Techniques in Smartphone Cameras
Image Processing for Augmented Reality: Real-time Object Overlay
The Development of Image Processing Algorithms for Traffic Control Systems
Pattern Recognition and Analysis in Forensic Imaging
Adaptive Filtering Techniques in Image Processing
Image Processing in Retail: Customer Tracking and Behavior Analysis
The Role of Image Processing in Cultural Heritage Preservation
Image Segmentation Techniques for Cancer Detection in Medical Imaging
High Dynamic Range (HDR) Imaging: Algorithms and Display Techniques
Image Classification with Deep Convolutional Neural Networks
The Evolution of Edge Detection Algorithms in Image Processing
Image Processing for Wildlife Monitoring: Species Recognition and Behavior Analysis
Application of Wavelet Transforms in Image Compression
Image Processing in Sports: Enhancing Broadcasts and Performance Analysis
Optical Character Recognition (OCR) Improvements in Document Scanning
Multi-Spectral Imaging for Environmental and Earth Studies
Image Processing for Space Exploration: Analysis of Planetary Images
Real-Time Image Processing for Event Surveillance
The Influence of Quantum Computing on Image Processing Speed and Security
Machine Vision in Manufacturing: Defect Detection and Quality Control
Image Processing in Neurology: Visualizing Brain Functions
Photogrammetry and Image Processing in Geology: 3D Terrain Mapping
Advanced Techniques in Image Watermarking for Copyright Protection
The Future of Image Processing: Integrating AI for Automated Editing
The Evolution of Enterprise Resource Planning (ERP) Systems in the Digital Age
Information Systems for Managing Distributed Workforces
The Role of Information Systems in Enhancing Supply Chain Management
Cybersecurity Measures in Information Systems
The Impact of Big Data on Decision Support Systems
Blockchain Technology for Information System Security
The Development of Sustainable IT Infrastructure in Information Systems
The Use of AI in Information Systems for Business Intelligence
Information Systems in Healthcare: Improving Patient Care and Data Management
The Influence of IoT on Information Systems Architecture
Mobile Information Systems: Development and Usability Challenges
The Role of Geographic Information Systems (GIS) in Urban Planning
Social Media Analytics: Tools and Techniques in Information Systems
Information Systems in Education: Enhancing Learning and Administration
Cloud Computing Integration into Corporate Information Systems
Information Systems Audit: Practices and Challenges
User Interface Design and User Experience in Information Systems
Privacy and Data Protection in Information Systems
The Future of Quantum Computing in Information Systems
The Role of Information Systems in Environmental Management
Implementing Effective Knowledge Management Systems
The Adoption of Virtual Reality in Information Systems
The Challenges of Implementing ERP Systems in Multinational Corporations
Information Systems for Real-Time Business Analytics
The Impact of 5G Technology on Mobile Information Systems
Ethical Issues in the Management of Information Systems
Information Systems in Retail: Enhancing Customer Experience and Management
The Role of Information Systems in Non-Profit Organizations
Development of Decision Support Systems for Strategic Planning
Information Systems in the Banking Sector: Enhancing Financial Services
Risk Management in Information Systems
The Integration of Artificial Neural Networks in Information Systems
Information Systems and Corporate Governance
Information Systems for Disaster Response and Management
The Role of Information Systems in Sports Management
Information Systems for Public Health Surveillance
The Future of Information Systems: Trends and Predictions
Information Systems in the Film and Media Industry
Business Process Reengineering through Information Systems
Implementing Customer Relationship Management (CRM) Systems in E-commerce
Emerging Trends in Artificial Intelligence and Machine Learning
The Future of Cloud Services and Technology
Cybersecurity: Current Threats and Future Defenses
The Role of Information Technology in Sustainable Energy Solutions
Internet of Things (IoT): From Smart Homes to Smart Cities
Blockchain and Its Impact on Information Technology
The Use of Big Data Analytics in Predictive Modeling
Virtual Reality (VR) and Augmented Reality (AR): The Next Frontier in IT
The Challenges of Digital Transformation in Traditional Businesses
Wearable Technology: Health Monitoring and Beyond
5G Technology: Implementation and Impacts on IT
Biometrics Technology: Uses and Privacy Concerns
The Role of IT in Global Health Initiatives
Ethical Considerations in the Development of Autonomous Systems
Data Privacy in the Age of Information Overload
The Evolution of Software Development Methodologies
Quantum Computing: The Next Revolution in IT
IT Governance: Best Practices and Standards
The Integration of AI in Customer Service Technology
IT in Manufacturing: Industrial Automation and Robotics
The Future of E-commerce: Technology and Trends
Mobile Computing: Innovations and Challenges
Information Technology in Education: Tools and Trends
IT Project Management: Approaches and Tools
The Role of IT in Media and Entertainment
The Impact of Digital Marketing Technologies on Business Strategies
IT in Logistics and Supply Chain Management
The Development and Future of Autonomous Vehicles
IT in the Insurance Sector: Enhancing Efficiency and Customer Engagement
The Role of IT in Environmental Conservation
Smart Grid Technology: IT at the Intersection of Energy Management
Telemedicine: The Impact of IT on Healthcare Delivery
IT in the Agricultural Sector: Innovations and Impact
Cyber-Physical Systems: IT in the Integration of Physical and Digital Worlds
The Influence of Social Media Platforms on IT Development
Data Centers: Evolution, Technologies, and Sustainability
IT in Public Administration: Improving Services and Transparency
The Role of IT in Sports Analytics
Information Technology in Retail: Enhancing the Shopping Experience
The Future of IT: Integrating Ethical AI Systems

Internet of Things (IoT) Thesis Topics

Enhancing IoT Security: Strategies for Safeguarding Connected Devices
IoT in Smart Cities: Infrastructure and Data Management Challenges
The Application of IoT in Precision Agriculture: Maximizing Efficiency and Yield
IoT and Healthcare: Opportunities for Remote Monitoring and Patient Care
Energy Efficiency in IoT: Techniques for Reducing Power Consumption in Devices
The Role of IoT in Supply Chain Management and Logistics
Real-Time Data Processing Using Edge Computing in IoT Networks
Privacy Concerns and Data Protection in IoT Systems
The Integration of IoT with Blockchain for Enhanced Security and Transparency
IoT in Environmental Monitoring: Systems for Air Quality and Water Safety
Predictive Maintenance in Industrial IoT: Strategies and Benefits
IoT in Retail: Enhancing Customer Experience through Smart Technology
The Development of Standard Protocols for IoT Communication
IoT in Smart Homes: Automation and Security Systems
The Role of IoT in Disaster Management: Early Warning Systems and Response Coordination
Machine Learning Techniques for IoT Data Analytics
IoT in Automotive: The Future of Connected and Autonomous Vehicles
The Impact of 5G on IoT: Enhancements in Speed and Connectivity
IoT Device Lifecycle Management: From Creation to Decommissioning
IoT in Public Safety: Applications for Emergency Response and Crime Prevention
The Ethics of IoT: Balancing Innovation with Consumer Rights
IoT and the Future of Work: Automation and Labor Market Shifts
Designing User-Friendly Interfaces for IoT Applications
IoT in the Energy Sector: Smart Grids and Renewable Energy Integration
Quantum Computing and IoT: Potential Impacts and Applications
The Role of AI in Enhancing IoT Solutions
IoT for Elderly Care: Technologies for Health and Mobility Assistance
IoT in Education: Enhancing Classroom Experiences and Learning Outcomes
Challenges in Scaling IoT Infrastructure for Global Coverage
The Economic Impact of IoT: Industry Transformations and New Business Models
IoT and Tourism: Enhancing Visitor Experiences through Connected Technologies
Data Fusion Techniques in IoT: Integrating Diverse Data Sources
IoT in Aquaculture: Monitoring and Managing Aquatic Environments
Wireless Technologies for IoT: Comparing LoRa, Zigbee, and NB-IoT
IoT and Intellectual Property: Navigating the Legal Landscape
IoT in Sports: Enhancing Training and Audience Engagement
Building Resilient IoT Systems against Cyber Attacks
IoT for Waste Management: Innovations and System Implementations
IoT in Agriculture: Drones and Sensors for Crop Monitoring
The Role of IoT in Cultural Heritage Preservation: Monitoring and Maintenance
Advanced Algorithms for Supervised and Unsupervised Learning
Machine Learning in Genomics: Predicting Disease Propensity and Treatment Outcomes
The Use of Neural Networks in Image Recognition and Analysis
Reinforcement Learning: Applications in Robotics and Autonomous Systems
The Role of Machine Learning in Natural Language Processing and Linguistic Analysis
Deep Learning for Predictive Analytics in Business and Finance
Machine Learning for Cybersecurity: Detection of Anomalies and Malware
Ethical Considerations in Machine Learning: Bias and Fairness
The Integration of Machine Learning with IoT for Smart Device Management
Transfer Learning: Techniques and Applications in New Domains
The Application of Machine Learning in Environmental Science
Machine Learning in Healthcare: Diagnosing Conditions from Medical Images
The Use of Machine Learning in Algorithmic Trading and Stock Market Analysis
Machine Learning in Social Media: Sentiment Analysis and Trend Prediction
Quantum Machine Learning: Merging Quantum Computing with AI
Feature Engineering and Selection in Machine Learning
Machine Learning for Enhancing User Experience in Mobile Applications
The Impact of Machine Learning on Digital Marketing Strategies
Machine Learning for Energy Consumption Forecasting and Optimization
The Role of Machine Learning in Enhancing Network Security Protocols
Scalability and Efficiency of Machine Learning Algorithms
Machine Learning in Drug Discovery and Pharmaceutical Research
The Application of Machine Learning in Sports Analytics
Machine Learning for Real-Time Decision-Making in Autonomous Vehicles
The Use of Machine Learning in Predicting Geographical and Meteorological Events
Machine Learning for Educational Data Mining and Learning Analytics
The Role of Machine Learning in Audio Signal Processing
Predictive Maintenance in Manufacturing Through Machine Learning
Machine Learning and Its Implications for Privacy and Surveillance
The Application of Machine Learning in Augmented Reality Systems
Deep Learning Techniques in Medical Diagnosis: Challenges and Opportunities
The Use of Machine Learning in Video Game Development
Machine Learning for Fraud Detection in Financial Services
The Role of Machine Learning in Agricultural Optimization and Management
The Impact of Machine Learning on Content Personalization and Recommendation Systems
Machine Learning in Legal Tech: Document Analysis and Case Prediction
Adaptive Learning Systems: Tailoring Education Through Machine Learning
Machine Learning in Space Exploration: Analyzing Data from Space Missions
Machine Learning for Public Sector Applications: Improving Services and Efficiency
The Future of Machine Learning: Integrating Explainable AI
Innovations in Convolutional Neural Networks for Image and Video Analysis
Recurrent Neural Networks: Applications in Sequence Prediction and Analysis
The Role of Neural Networks in Predicting Financial Market Trends
Deep Neural Networks for Enhanced Speech Recognition Systems
Neural Networks in Medical Imaging: From Detection to Diagnosis
Generative Adversarial Networks (GANs): Applications in Art and Media
The Use of Neural Networks in Autonomous Driving Technologies
Neural Networks for Real-Time Language Translation
The Application of Neural Networks in Robotics: Sensory Data and Movement Control
Neural Network Optimization Techniques: Overcoming Overfitting and Underfitting
The Integration of Neural Networks with Blockchain for Data Security
Neural Networks in Climate Modeling and Weather Forecasting
The Use of Neural Networks in Enhancing Internet of Things (IoT) Devices
Graph Neural Networks: Applications in Social Network Analysis and Beyond
The Impact of Neural Networks on Augmented Reality Experiences
Neural Networks for Anomaly Detection in Network Security
The Application of Neural Networks in Bioinformatics and Genomic Data Analysis
Capsule Neural Networks: Improving the Robustness and Interpretability of Deep Learning
The Role of Neural Networks in Consumer Behavior Analysis
Neural Networks in Energy Sector: Forecasting and Optimization
The Evolution of Neural Network Architectures for Efficient Learning
The Use of Neural Networks in Sentiment Analysis: Techniques and Challenges
Deep Reinforcement Learning: Strategies for Advanced Decision-Making Systems
Neural Networks for Precision Medicine: Tailoring Treatments to Individual Genetic Profiles
The Use of Neural Networks in Virtual Assistants: Enhancing Natural Language Understanding
The Impact of Neural Networks on Pharmaceutical Research
Neural Networks for Supply Chain Management: Prediction and Automation
The Application of Neural Networks in E-commerce: Personalization and Recommendation Systems
Neural Networks for Facial Recognition: Advances and Ethical Considerations
The Role of Neural Networks in Educational Technologies
The Use of Neural Networks in Predicting Economic Trends
Neural Networks in Sports: Analyzing Performance and Strategy
The Impact of Neural Networks on Digital Security Systems
Neural Networks for Real-Time Video Surveillance Analysis
The Integration of Neural Networks in Edge Computing Devices
Neural Networks for Industrial Automation: Improving Efficiency and Accuracy
The Future of Neural Networks: Towards More General AI Applications
Neural Networks in Art and Design: Creating New Forms of Expression
The Role of Neural Networks in Enhancing Public Health Initiatives
The Future of Neural Networks: Challenges in Scalability and Generalization
The Evolution of Programming Paradigms: Functional vs. Object-Oriented Programming
Advances in Compiler Design and Optimization Techniques
The Impact of Programming Languages on Software Security
Developing Programming Languages for Quantum Computing
Machine Learning in Automated Code Generation and Optimization
The Role of Programming in Developing Scalable Cloud Applications
The Future of Web Development: New Frameworks and Technologies
Cross-Platform Development: Best Practices in Mobile App Programming
The Influence of Programming Techniques on Big Data Analytics
Real-Time Systems Programming: Challenges and Solutions
The Integration of Programming with Blockchain Technology
Programming for IoT: Languages and Tools for Device Communication
Secure Coding Practices: Preventing Cyber Attacks through Software Design
The Role of Programming in Data Visualization and User Interface Design
Advances in Game Programming: Graphics, AI, and Network Play
The Impact of Programming on Digital Media and Content Creation
Programming Languages for Robotics: Trends and Future Directions
The Use of Artificial Intelligence in Enhancing Programming Productivity
Programming for Augmented and Virtual Reality: New Challenges and Techniques
Ethical Considerations in Programming: Bias, Fairness, and Transparency
The Future of Programming Education: Interactive and Adaptive Learning Models
Programming for Wearable Technology: Special Considerations and Challenges
The Evolution of Programming in Financial Technology
Functional Programming in Enterprise Applications
Memory Management Techniques in Programming: From Garbage Collection to Manual Control
The Role of Open Source Programming in Accelerating Innovation
The Impact of Programming on Network Security and Cryptography
Developing Accessible Software: Programming for Users with Disabilities
Programming Language Theories: New Models and Approaches
The Challenges of Legacy Code: Strategies for Modernization and Integration
Energy-Efficient Programming: Optimizing Code for Green Computing
Multithreading and Concurrency: Advanced Programming Techniques
The Impact of Programming on Computational Biology and Bioinformatics
The Role of Scripting Languages in Automating System Administration
Programming and the Future of Quantum Resistant Cryptography
Code Review and Quality Assurance: Techniques and Tools
Adaptive and Predictive Programming for Dynamic Environments
The Role of Programming in Enhancing E-commerce Technology
Programming for Cyber-Physical Systems: Bridging the Gap Between Digital and Physical
The Influence of Programming Languages on Computational Efficiency and Performance
Quantum Algorithms: Development and Applications Beyond Shor’s and Grover’s Algorithms
The Role of Quantum Computing in Solving Complex Biological Problems
Quantum Cryptography: New Paradigms for Secure Communication
Error Correction Techniques in Quantum Computing
Quantum Computing and Its Impact on Artificial Intelligence
The Integration of Classical and Quantum Computing: Hybrid Models
Quantum Machine Learning: Theoretical Foundations and Practical Applications
Quantum Computing Hardware: Advances in Qubit Technology
The Application of Quantum Computing in Financial Modeling and Risk Assessment
Quantum Networking: Establishing Secure Quantum Communication Channels
The Future of Drug Discovery: Applications of Quantum Computing
Quantum Computing in Cryptanalysis: Threats to Current Cryptography Standards
Simulation of Quantum Systems for Material Science
Quantum Computing for Optimization Problems in Logistics and Manufacturing
Theoretical Limits of Quantum Computing: Understanding Quantum Complexity
Quantum Computing and the Future of Search Algorithms
The Role of Quantum Computing in Climate Science and Environmental Modeling
Quantum Annealing vs. Universal Quantum Computing: Comparative Studies
Implementing Quantum Algorithms in Quantum Programming Languages
The Impact of Quantum Computing on Public Key Cryptography
Quantum Entanglement: Experiments and Applications in Quantum Networks
Scalability Challenges in Quantum Processors
The Ethics and Policy Implications of Quantum Computing
Quantum Computing in Space Exploration and Astrophysics
The Role of Quantum Computing in Developing Next-Generation AI Systems
Quantum Computing in the Energy Sector: Applications in Smart Grids and Nuclear Fusion
Noise and Decoherence in Quantum Computers: Overcoming Practical Challenges
Quantum Computing for Predicting Economic Market Trends
Quantum Sensors: Enhancing Precision in Measurement and Imaging
The Future of Quantum Computing Education and Workforce Development
Quantum Computing in Cybersecurity: Preparing for a Post-Quantum World
Quantum Computing and the Internet of Things: Potential Intersections
Practical Quantum Computing: From Theory to Real-World Applications
Quantum Supremacy: Milestones and Future Goals
The Role of Quantum Computing in Genetics and Genomics
Quantum Computing for Material Discovery and Design
The Challenges of Quantum Programming Languages and Environments
Quantum Computing in Art and Creative Industries
The Global Race for Quantum Computing Supremacy: Technological and Political Aspects
Quantum Computing and Its Implications for Software Engineering
Advances in Humanoid Robotics: New Developments and Challenges
Robotics in Healthcare: From Surgery to Rehabilitation
The Integration of AI in Robotics: Enhanced Autonomy and Learning Capabilities
Swarm Robotics: Coordination Strategies and Applications
The Use of Robotics in Hazardous Environments: Deep Sea and Space Exploration
Soft Robotics: Materials, Design, and Applications
Robotics in Agriculture: Automation of Farming and Harvesting Processes
The Role of Robotics in Manufacturing: Increased Efficiency and Flexibility
Ethical Considerations in the Deployment of Robots in Human Environments
Autonomous Vehicles: Technological Advances and Regulatory Challenges
Robotic Assistants for the Elderly and Disabled: Improving Quality of Life
The Use of Robotics in Education: Teaching Science, Technology, Engineering, and Math (STEM)
Robotics and Computer Vision: Enhancing Perception and Decision Making
The Impact of Robotics on Employment and the Workforce
The Development of Robotic Systems for Environmental Monitoring and Conservation
Machine Learning Techniques for Robotic Perception and Navigation
Advances in Robotic Surgery: Precision and Outcomes
Human-Robot Interaction: Building Trust and Cooperation
Robotics in Retail: Automated Warehousing and Customer Service
Energy-Efficient Robots: Design and Utilization
Robotics in Construction: Automation and Safety Improvements
The Role of Robotics in Disaster Response and Recovery Operations
The Application of Robotics in Art and Creative Industries
Robotics and the Future of Personal Transportation
Ethical AI in Robotics: Ensuring Safe and Fair Decision-Making
The Use of Robotics in Logistics: Drones and Autonomous Delivery Vehicles
Robotics in the Food Industry: From Production to Service
The Integration of IoT with Robotics for Enhanced Connectivity
Wearable Robotics: Exoskeletons for Rehabilitation and Enhanced Mobility
The Impact of Robotics on Privacy and Security
Robotic Pet Companions: Social Robots and Their Psychological Effects
Robotics for Planetary Exploration and Colonization
Underwater Robotics: Innovations in Oceanography and Marine Biology
Advances in Robotics Programming Languages and Tools
The Role of Robotics in Minimizing Human Exposure to Contaminants and Pathogens
Collaborative Robots (Cobots): Working Alongside Humans in Shared Spaces
The Use of Robotics in Entertainment and Sports
Robotics and Machine Ethics: Programming Moral Decision-Making
The Future of Military Robotics: Opportunities and Challenges
Sustainable Robotics: Reducing the Environmental Impact of Robotic Systems
Agile Methodologies: Evolution and Future Trends
DevOps Practices: Improving Software Delivery and Lifecycle Management
The Impact of Microservices Architecture on Software Development
Containerization Technologies: Docker, Kubernetes, and Beyond
Software Quality Assurance: Modern Techniques and Tools
The Role of Artificial Intelligence in Automated Software Testing
Blockchain Applications in Software Development and Security
The Integration of Continuous Integration and Continuous Deployment (CI/CD) in Software Projects
Cybersecurity in Software Engineering: Best Practices for Secure Coding
Low-Code and No-Code Development: Implications for Professional Software Development
The Future of Software Engineering Education
Software Sustainability: Developing Green Software and Reducing Carbon Footprints
The Role of Software Engineering in Healthcare: Telemedicine and Patient Data Management
Privacy by Design: Incorporating Privacy Features at the Development Stage
The Impact of Quantum Computing on Software Engineering
Software Engineering for Augmented and Virtual Reality: Challenges and Innovations
Cloud-Native Applications: Design, Development, and Deployment
Software Project Management: Agile vs. Traditional Approaches
Open Source Software: Community Engagement and Project Sustainability
The Evolution of Graphical User Interfaces in Application Development
The Challenges of Integrating IoT Devices into Software Systems
Ethical Issues in Software Engineering: Bias, Accountability, and Regulation
Software Engineering for Autonomous Vehicles: Safety and Regulatory Considerations
Big Data Analytics in Software Development: Enhancing Decision-Making Processes
The Future of Mobile App Development: Trends and Technologies
The Role of Software Engineering in Artificial Intelligence: Frameworks and Algorithms
Performance Optimization in Software Applications
Adaptive Software Development: Responding to Changing User Needs
Software Engineering in Financial Services: Compliance and Security Challenges
User Experience (UX) Design in Software Engineering
The Role of Software Engineering in Smart Cities: Infrastructure and Services
The Impact of 5G on Software Development and Deployment
Real-Time Systems in Software Engineering: Design and Implementation Challenges
Cross-Platform Development Challenges: Ensuring Consistency and Performance
Software Testing Automation: Tools and Trends
The Integration of Cyber-Physical Systems in Software Engineering
Software Engineering in the Entertainment Industry: Game Development and Beyond
The Application of Machine Learning in Predicting Software Bugs
The Role of Software Engineering in Cybersecurity Defense Strategies
Accessibility in Software Engineering: Creating Inclusive and Usable Software
Progressive Web Apps (PWAs): Advantages and Implementation Challenges
The Future of Web Accessibility: Standards and Practices
Single-Page Applications (SPAs) vs. Multi-Page Applications (MPAs): Performance and Usability
The Impact of Serverless Computing on Web Development
The Evolution of CSS for Modern Web Design
Security Best Practices in Web Development: Defending Against XSS and CSRF Attacks
The Role of Web Development in Enhancing E-commerce User Experience
The Use of Artificial Intelligence in Web Personalization and User Engagement
The Future of Web APIs: Standards, Security, and Scalability
Responsive Web Design: Techniques and Trends
JavaScript Frameworks: Vue.js, React.js, and Angular – A Comparative Analysis
Web Development for IoT: Interfaces and Connectivity Solutions
The Impact of 5G on Web Development and User Experiences
The Use of Blockchain Technology in Web Development for Enhanced Security
Web Development in the Cloud: Using AWS, Azure, and Google Cloud
Content Management Systems (CMS): Trends and Future Developments
The Application of Web Development in Virtual and Augmented Reality
The Importance of Web Performance Optimization: Tools and Techniques
Sustainable Web Design: Practices for Reducing Energy Consumption
The Role of Web Development in Digital Marketing: SEO and Social Media Integration
Headless CMS: Benefits and Challenges for Developers and Content Creators
The Future of Web Typography: Design, Accessibility, and Performance
Web Development and Data Protection: Complying with GDPR and Other Regulations
Real-Time Web Communication: Technologies like WebSockets and WebRTC
Front-End Development Tools: Efficiency and Innovation in Workflow
The Challenges of Migrating Legacy Systems to Modern Web Architectures
Microfrontends Architecture: Designing Scalable and Decoupled Web Applications
The Impact of Cryptocurrencies on Web Payment Systems
User-Centered Design in Web Development: Methods for Engaging Users
The Role of Web Development in Business Intelligence: Dashboards and Reporting Tools
Web Development for Mobile Platforms: Optimization and Best Practices
The Evolution of E-commerce Platforms: From Web to Mobile Commerce
Web Security in E-commerce: Protecting Transactions and User Data
Dynamic Web Content: Server-Side vs. Client-Side Rendering
The Future of Full Stack Development: Trends and Skills
Web Design Psychology: How Design Influences User Behavior
The Role of Web Development in the Non-Profit Sector: Fundraising and Community Engagement
The Integration of AI Chatbots in Web Development
The Use of Motion UI in Web Design: Enhancing Aesthetics and User Interaction
The Future of Web Development: Predictions and Emerging Technologies

We trust that this comprehensive list of computer science thesis topics will serve as a valuable starting point for your research endeavors. With 1000 unique and carefully selected topics distributed across 25 key areas of computer science, students are equipped to tackle complex questions and contribute meaningful advancements to the field. As you proceed to select your thesis topic, consider not only your personal interests and career goals but also the potential impact of your research. We encourage you to explore these topics thoroughly and choose one that will not only challenge you but also push the boundaries of technology and innovation.

The Range of Computer Science Thesis Topics

Computer science stands as a dynamic and ever-evolving field that continuously reshapes how we interact with the world. At its core, the discipline encompasses not just the study of algorithms and computation, but a broad spectrum of practical and theoretical knowledge areas that drive innovation in various sectors. This article aims to explore the rich landscape of computer science thesis topics, offering students and researchers a glimpse into the potential areas of study that not only challenge the intellect but also contribute significantly to technological progress. As we delve into the current issues, recent trends, and future directions of computer science, it becomes evident that the possibilities for research are both vast and diverse. Whether you are intrigued by the complexities of artificial intelligence, the robust architecture of networks and systems, or the innovative approaches in cybersecurity, computer science offers a fertile ground for developing thesis topics that are as impactful as they are intellectually stimulating.

Current Issues in Computer Science

One of the prominent current issues in computer science revolves around data security and privacy. As digital transformation accelerates across industries, the massive influx of data generated poses significant challenges in terms of its protection and ethical use. Cybersecurity threats have become more sophisticated, with data breaches and cyber-attacks causing major concerns for organizations worldwide. This ongoing battle demands continuous improvements in security protocols and the development of robust cybersecurity measures. Computer science thesis topics in this area can explore new cryptographic methods, intrusion detection systems, and secure communication protocols to fortify digital defenses. Research could also delve into the ethical implications of data collection and use, proposing frameworks that ensure privacy while still leveraging data for innovation.

Another critical issue facing the field of computer science is the ethical development and deployment of artificial intelligence (AI) systems. As AI technologies become more integrated into daily life and critical infrastructure, concerns about bias, fairness, and accountability in AI systems have intensified. Thesis topics could focus on developing algorithms that address these ethical concerns, including techniques for reducing bias in machine learning models and methods for increasing transparency and explainability in AI decisions. This research is crucial for ensuring that AI technologies promote fairness and do not perpetuate or exacerbate existing societal inequalities.

Furthermore, the rapid pace of technological change presents a challenge in terms of sustainability and environmental impact. The energy consumption of large data centers, the carbon footprint of producing and disposing of electronic waste, and the broader effects of high-tech innovations on the environment are significant concerns within computer science. Thesis research in this domain could focus on creating more energy-efficient computing methods, developing algorithms that reduce power consumption, or innovating recycling technologies that address the issue of e-waste. This research not only contributes to the field of computer science but also plays a crucial role in ensuring that technological advancement does not come at an unsustainable cost to the environment.

These current issues highlight the dynamic nature of computer science and its direct impact on society. Addressing these challenges through focused research and innovative thesis topics not only advances the field but also contributes to resolving some of the most pressing problems facing our global community today.

Recent Trends in Computer Science

In recent years, computer science has witnessed significant advancements in the integration of artificial intelligence (AI) and machine learning (ML) across various sectors, marking one of the most exciting trends in the field. These technologies are not just reshaping traditional industries but are also at the forefront of driving innovations in areas like healthcare, finance, and autonomous systems. Thesis topics within this trend could explore the development of advanced ML algorithms that enhance predictive analytics, improve automated decision-making, or refine natural language processing capabilities. Additionally, AI’s role in ethical decision-making and its societal impacts offers a rich vein of inquiry for research, focusing on mitigating biases and ensuring that AI systems operate transparently and justly.

Another prominent trend in computer science is the rapid growth of blockchain technology beyond its initial application in cryptocurrencies. Blockchain is proving its potential in creating more secure, decentralized, and transparent networks for a variety of applications, from enhancing supply chain logistics to revolutionizing digital identity verification processes. Computer science thesis topics could investigate novel uses of blockchain for ensuring data integrity in digital transactions, enhancing cybersecurity measures, or even developing new frameworks for blockchain integration into existing technological infrastructures. The exploration of blockchain’s scalability, speed, and energy consumption also presents critical research opportunities that are timely and relevant.

Furthermore, the expansion of the Internet of Things (IoT) continues to be a significant trend, with more devices becoming connected every day, leading to increasingly smart environments. This proliferation poses unique challenges and opportunities for computer science research, particularly in terms of scalability, security, and new data management strategies. Thesis topics might focus on optimizing network protocols to handle the massive influx of data from IoT devices, developing solutions to safeguard against IoT-specific security vulnerabilities, or innovative applications of IoT in urban planning, smart homes, or healthcare. Research in this area is crucial for advancing the efficiency and functionality of IoT systems and for ensuring they can be safely and effectively integrated into modern life.

These recent trends underscore the vibrant and ever-evolving nature of computer science, reflecting its capacity to influence and transform an array of sectors through technological innovation. The continual emergence of new research topics within these trends not only enriches the academic discipline but also provides substantial benefits to society by addressing practical challenges and enhancing the capabilities of technology in everyday life.

Future Directions in Computer Science

As we look toward the future, one of the most anticipated areas in computer science is the advancement of quantum computing. This emerging technology promises to revolutionize problem-solving in fields that require immense computational power, such as cryptography, drug discovery, and complex system modeling. Quantum computing has the potential to process tasks at speeds unachievable by classical computers, offering breakthroughs in materials science and encryption methods. Computer science thesis topics might explore the theoretical underpinnings of quantum algorithms, the development of quantum-resistant cryptographic systems, or practical applications of quantum computing in industry-specific scenarios. Research in this area not only contributes to the foundational knowledge of quantum mechanics but also paves the way for its integration into mainstream computing, marking a significant leap forward in computational capabilities.

Another promising direction in computer science is the advancement of autonomous systems, particularly in robotics and vehicle automation. The future of autonomous technologies hinges on improving their safety, reliability, and decision-making processes under uncertain conditions. Thesis topics could focus on the enhancement of machine perception through computer vision and sensor fusion, the development of more sophisticated AI-driven decision frameworks, or ethical considerations in the deployment of autonomous systems. As these technologies become increasingly prevalent, research will play a crucial role in addressing the societal and technical challenges they present, ensuring their beneficial integration into daily life and industry operations.

Additionally, the ongoing expansion of artificial intelligence applications poses significant future directions for research, especially in the realm of AI ethics and policy. As AI systems become more capable and widespread, their impact on privacy, employment, and societal norms continues to grow. Future thesis topics might delve into the development of guidelines and frameworks for responsible AI, studies on the impact of AI on workforce dynamics, or innovations in transparent and fair AI systems. This research is vital for guiding the ethical evolution of AI technologies, ensuring they enhance societal well-being without diminishing human dignity or autonomy.

These future directions in computer science not only highlight the field’s potential for substantial technological advancements but also underscore the importance of thoughtful consideration of their broader implications. By exploring these areas in depth, computer science research can lead the way in not just technological innovation, but also in shaping a future where technology and ethics coexist harmoniously for the betterment of society.

In conclusion, the field of computer science is not only foundational to the technological advancements that characterize the modern age but also crucial in solving some of the most pressing challenges of our time. The potential thesis topics discussed in this article reflect a mere fraction of the opportunities that lie in the realms of theory, application, and innovation within this expansive field. As emerging technologies such as quantum computing, artificial intelligence, and blockchain continue to evolve, they open new avenues for research that could potentially redefine existing paradigms. For students embarking on their thesis journey, it is essential to choose a topic that not only aligns with their academic passions but also contributes to the ongoing expansion of computer science knowledge. By pushing the boundaries of what is known and exploring uncharted territories, students can leave a lasting impact on the field and pave the way for future technological breakthroughs. As we look forward, it’s clear that computer science will continue to be a key driver of change, making it an exciting and rewarding area for academic and professional growth.

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Machine Learning - CMU

PhD Dissertations

[all are .pdf files].

Learning Models that Match Jacob Tyo, 2024

Improving Human Integration across the Machine Learning Pipeline Charvi Rastogi, 2024

Reliable and Practical Machine Learning for Dynamic Healthcare Settings Helen Zhou, 2023

Automatic customization of large-scale spiking network models to neuronal population activity (unavailable) Shenghao Wu, 2023

Estimation of BVk functions from scattered data (unavailable) Addison J. Hu, 2023

Rethinking object categorization in computer vision (unavailable) Jayanth Koushik, 2023

Advances in Statistical Gene Networks Jinjin Tian, 2023 Post-hoc calibration without distributional assumptions Chirag Gupta, 2023

The Role of Noise, Proxies, and Dynamics in Algorithmic Fairness Nil-Jana Akpinar, 2023

Collaborative learning by leveraging siloed data Sebastian Caldas, 2023

Modeling Epidemiological Time Series Aaron Rumack, 2023

Human-Centered Machine Learning: A Statistical and Algorithmic Perspective Leqi Liu, 2023

Uncertainty Quantification under Distribution Shifts Aleksandr Podkopaev, 2023

Probabilistic Reinforcement Learning: Using Data to Define Desired Outcomes, and Inferring How to Get There Benjamin Eysenbach, 2023

Comparing Forecasters and Abstaining Classifiers Yo Joong Choe, 2023

Using Task Driven Methods to Uncover Representations of Human Vision and Semantics Aria Yuan Wang, 2023

Data-driven Decisions - An Anomaly Detection Perspective Shubhranshu Shekhar, 2023

Applied Mathematics of the Future Kin G. Olivares, 2023

METHODS AND APPLICATIONS OF EXPLAINABLE MACHINE LEARNING Joon Sik Kim, 2023

NEURAL REASONING FOR QUESTION ANSWERING Haitian Sun, 2023

Principled Machine Learning for Societally Consequential Decision Making Amanda Coston, 2023

Long term brain dynamics extend cognitive neuroscience to timescales relevant for health and physiology Maxwell B. Wang, 2023

Long term brain dynamics extend cognitive neuroscience to timescales relevant for health and physiology Darby M. Losey, 2023

Calibrated Conditional Density Models and Predictive Inference via Local Diagnostics David Zhao, 2023

Towards an Application-based Pipeline for Explainability Gregory Plumb, 2022

Objective Criteria for Explainable Machine Learning Chih-Kuan Yeh, 2022

Making Scientific Peer Review Scientific Ivan Stelmakh, 2022

Facets of regularization in high-dimensional learning: Cross-validation, risk monotonization, and model complexity Pratik Patil, 2022

Active Robot Perception using Programmable Light Curtains Siddharth Ancha, 2022

Strategies for Black-Box and Multi-Objective Optimization Biswajit Paria, 2022

Unifying State and Policy-Level Explanations for Reinforcement Learning Nicholay Topin, 2022

Sensor Fusion Frameworks for Nowcasting Maria Jahja, 2022

Equilibrium Approaches to Modern Deep Learning Shaojie Bai, 2022

Towards General Natural Language Understanding with Probabilistic Worldbuilding Abulhair Saparov, 2022

Applications of Point Process Modeling to Spiking Neurons (Unavailable) Yu Chen, 2021

Neural variability: structure, sources, control, and data augmentation Akash Umakantha, 2021

Structure and time course of neural population activity during learning Jay Hennig, 2021

Cross-view Learning with Limited Supervision Yao-Hung Hubert Tsai, 2021

Meta Reinforcement Learning through Memory Emilio Parisotto, 2021

Learning Embodied Agents with Scalably-Supervised Reinforcement Learning Lisa Lee, 2021

Learning to Predict and Make Decisions under Distribution Shift Yifan Wu, 2021

Statistical Game Theory Arun Sai Suggala, 2021

Towards Knowledge-capable AI: Agents that See, Speak, Act and Know Kenneth Marino, 2021

Learning and Reasoning with Fast Semidefinite Programming and Mixing Methods Po-Wei Wang, 2021

Bridging Language in Machines with Language in the Brain Mariya Toneva, 2021

Curriculum Learning Otilia Stretcu, 2021

Principles of Learning in Multitask Settings: A Probabilistic Perspective Maruan Al-Shedivat, 2021

Towards Robust and Resilient Machine Learning Adarsh Prasad, 2021

Towards Training AI Agents with All Types of Experiences: A Unified ML Formalism Zhiting Hu, 2021

Building Intelligent Autonomous Navigation Agents Devendra Chaplot, 2021

Learning to See by Moving: Self-supervising 3D Scene Representations for Perception, Control, and Visual Reasoning Hsiao-Yu Fish Tung, 2021

Statistical Astrophysics: From Extrasolar Planets to the Large-scale Structure of the Universe Collin Politsch, 2020

Causal Inference with Complex Data Structures and Non-Standard Effects Kwhangho Kim, 2020

Networks, Point Processes, and Networks of Point Processes Neil Spencer, 2020

Dissecting neural variability using population recordings, network models, and neurofeedback (Unavailable) Ryan Williamson, 2020

Predicting Health and Safety: Essays in Machine Learning for Decision Support in the Public Sector Dylan Fitzpatrick, 2020

Towards a Unified Framework for Learning and Reasoning Han Zhao, 2020

Learning DAGs with Continuous Optimization Xun Zheng, 2020

Machine Learning and Multiagent Preferences Ritesh Noothigattu, 2020

Learning and Decision Making from Diverse Forms of Information Yichong Xu, 2020

Towards Data-Efficient Machine Learning Qizhe Xie, 2020

Change modeling for understanding our world and the counterfactual one(s) William Herlands, 2020

Machine Learning in High-Stakes Settings: Risks and Opportunities Maria De-Arteaga, 2020

Data Decomposition for Constrained Visual Learning Calvin Murdock, 2020

Structured Sparse Regression Methods for Learning from High-Dimensional Genomic Data Micol Marchetti-Bowick, 2020

Towards Efficient Automated Machine Learning Liam Li, 2020

LEARNING COLLECTIONS OF FUNCTIONS Emmanouil Antonios Platanios, 2020

Provable, structured, and efficient methods for robustness of deep networks to adversarial examples Eric Wong , 2020

Reconstructing and Mining Signals: Algorithms and Applications Hyun Ah Song, 2020

Probabilistic Single Cell Lineage Tracing Chieh Lin, 2020

Graphical network modeling of phase coupling in brain activity (unavailable) Josue Orellana, 2019

Strategic Exploration in Reinforcement Learning - New Algorithms and Learning Guarantees Christoph Dann, 2019 Learning Generative Models using Transformations Chun-Liang Li, 2019

Estimating Probability Distributions and their Properties Shashank Singh, 2019

Post-Inference Methods for Scalable Probabilistic Modeling and Sequential Decision Making Willie Neiswanger, 2019

Accelerating Text-as-Data Research in Computational Social Science Dallas Card, 2019

Multi-view Relationships for Analytics and Inference Eric Lei, 2019

Information flow in networks based on nonstationary multivariate neural recordings Natalie Klein, 2019

Competitive Analysis for Machine Learning & Data Science Michael Spece, 2019

The When, Where and Why of Human Memory Retrieval Qiong Zhang, 2019

Towards Effective and Efficient Learning at Scale Adams Wei Yu, 2019

Towards Literate Artificial Intelligence Mrinmaya Sachan, 2019

Learning Gene Networks Underlying Clinical Phenotypes Under SNP Perturbations From Genome-Wide Data Calvin McCarter, 2019

Unified Models for Dynamical Systems Carlton Downey, 2019

Anytime Prediction and Learning for the Balance between Computation and Accuracy Hanzhang Hu, 2019

Statistical and Computational Properties of Some "User-Friendly" Methods for High-Dimensional Estimation Alnur Ali, 2019

Nonparametric Methods with Total Variation Type Regularization Veeranjaneyulu Sadhanala, 2019

New Advances in Sparse Learning, Deep Networks, and Adversarial Learning: Theory and Applications Hongyang Zhang, 2019

Gradient Descent for Non-convex Problems in Modern Machine Learning Simon Shaolei Du, 2019

Selective Data Acquisition in Learning and Decision Making Problems Yining Wang, 2019

Anomaly Detection in Graphs and Time Series: Algorithms and Applications Bryan Hooi, 2019

Neural dynamics and interactions in the human ventral visual pathway Yuanning Li, 2018

Tuning Hyperparameters without Grad Students: Scaling up Bandit Optimisation Kirthevasan Kandasamy, 2018

Teaching Machines to Classify from Natural Language Interactions Shashank Srivastava, 2018

Statistical Inference for Geometric Data Jisu Kim, 2018

Representation Learning @ Scale Manzil Zaheer, 2018

Diversity-promoting and Large-scale Machine Learning for Healthcare Pengtao Xie, 2018

Distribution and Histogram (DIsH) Learning Junier Oliva, 2018

Stress Detection for Keystroke Dynamics Shing-Hon Lau, 2018

Sublinear-Time Learning and Inference for High-Dimensional Models Enxu Yan, 2018

Neural population activity in the visual cortex: Statistical methods and application Benjamin Cowley, 2018

Efficient Methods for Prediction and Control in Partially Observable Environments Ahmed Hefny, 2018

Learning with Staleness Wei Dai, 2018

Statistical Approach for Functionally Validating Transcription Factor Bindings Using Population SNP and Gene Expression Data Jing Xiang, 2017

New Paradigms and Optimality Guarantees in Statistical Learning and Estimation Yu-Xiang Wang, 2017

Dynamic Question Ordering: Obtaining Useful Information While Reducing User Burden Kirstin Early, 2017

New Optimization Methods for Modern Machine Learning Sashank J. Reddi, 2017

Active Search with Complex Actions and Rewards Yifei Ma, 2017

Why Machine Learning Works George D. Montañez , 2017

Source-Space Analyses in MEG/EEG and Applications to Explore Spatio-temporal Neural Dynamics in Human Vision Ying Yang , 2017

Computational Tools for Identification and Analysis of Neuronal Population Activity Pengcheng Zhou, 2016

Expressive Collaborative Music Performance via Machine Learning Gus (Guangyu) Xia, 2016

Supervision Beyond Manual Annotations for Learning Visual Representations Carl Doersch, 2016

Exploring Weakly Labeled Data Across the Noise-Bias Spectrum Robert W. H. Fisher, 2016

Optimizing Optimization: Scalable Convex Programming with Proximal Operators Matt Wytock, 2016

Combining Neural Population Recordings: Theory and Application William Bishop, 2015

Discovering Compact and Informative Structures through Data Partitioning Madalina Fiterau-Brostean, 2015

Machine Learning in Space and Time Seth R. Flaxman, 2015

The Time and Location of Natural Reading Processes in the Brain Leila Wehbe, 2015

Shape-Constrained Estimation in High Dimensions Min Xu, 2015

Spectral Probabilistic Modeling and Applications to Natural Language Processing Ankur Parikh, 2015 Computational and Statistical Advances in Testing and Learning Aaditya Kumar Ramdas, 2015

Corpora and Cognition: The Semantic Composition of Adjectives and Nouns in the Human Brain Alona Fyshe, 2015

Learning Statistical Features of Scene Images Wooyoung Lee, 2014

Towards Scalable Analysis of Images and Videos Bin Zhao, 2014

Statistical Text Analysis for Social Science Brendan T. O'Connor, 2014

Modeling Large Social Networks in Context Qirong Ho, 2014

Semi-Cooperative Learning in Smart Grid Agents Prashant P. Reddy, 2013

On Learning from Collective Data Liang Xiong, 2013

Exploiting Non-sequence Data in Dynamic Model Learning Tzu-Kuo Huang, 2013

Mathematical Theories of Interaction with Oracles Liu Yang, 2013

Short-Sighted Probabilistic Planning Felipe W. Trevizan, 2013

Statistical Models and Algorithms for Studying Hand and Finger Kinematics and their Neural Mechanisms Lucia Castellanos, 2013

Approximation Algorithms and New Models for Clustering and Learning Pranjal Awasthi, 2013

Uncovering Structure in High-Dimensions: Networks and Multi-task Learning Problems Mladen Kolar, 2013

Learning with Sparsity: Structures, Optimization and Applications Xi Chen, 2013

GraphLab: A Distributed Abstraction for Large Scale Machine Learning Yucheng Low, 2013

Graph Structured Normal Means Inference James Sharpnack, 2013 (Joint Statistics & ML PhD)

Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data Hai-Son Phuoc Le, 2013

Learning Large-Scale Conditional Random Fields Joseph K. Bradley, 2013

New Statistical Applications for Differential Privacy Rob Hall, 2013 (Joint Statistics & ML PhD)

Parallel and Distributed Systems for Probabilistic Reasoning Joseph Gonzalez, 2012

Spectral Approaches to Learning Predictive Representations Byron Boots, 2012

Attribute Learning using Joint Human and Machine Computation Edith L. M. Law, 2012

Statistical Methods for Studying Genetic Variation in Populations Suyash Shringarpure, 2012

Data Mining Meets HCI: Making Sense of Large Graphs Duen Horng (Polo) Chau, 2012

Learning with Limited Supervision by Input and Output Coding Yi Zhang, 2012

Target Sequence Clustering Benjamin Shih, 2011

Nonparametric Learning in High Dimensions Han Liu, 2010 (Joint Statistics & ML PhD)

Structural Analysis of Large Networks: Observations and Applications Mary McGlohon, 2010

Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy Brian D. Ziebart, 2010

Tractable Algorithms for Proximity Search on Large Graphs Purnamrita Sarkar, 2010

Rare Category Analysis Jingrui He, 2010

Coupled Semi-Supervised Learning Andrew Carlson, 2010

Fast Algorithms for Querying and Mining Large Graphs Hanghang Tong, 2009

Efficient Matrix Models for Relational Learning Ajit Paul Singh, 2009

Exploiting Domain and Task Regularities for Robust Named Entity Recognition Andrew O. Arnold, 2009

Theoretical Foundations of Active Learning Steve Hanneke, 2009

Generalized Learning Factors Analysis: Improving Cognitive Models with Machine Learning Hao Cen, 2009

Detecting Patterns of Anomalies Kaustav Das, 2009

Dynamics of Large Networks Jurij Leskovec, 2008

Computational Methods for Analyzing and Modeling Gene Regulation Dynamics Jason Ernst, 2008

Stacked Graphical Learning Zhenzhen Kou, 2007

Actively Learning Specific Function Properties with Applications to Statistical Inference Brent Bryan, 2007

Approximate Inference, Structure Learning and Feature Estimation in Markov Random Fields Pradeep Ravikumar, 2007

Scalable Graphical Models for Social Networks Anna Goldenberg, 2007

Measure Concentration of Strongly Mixing Processes with Applications Leonid Kontorovich, 2007

Tools for Graph Mining Deepayan Chakrabarti, 2005

Automatic Discovery of Latent Variable Models Ricardo Silva, 2005

Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic.

Overview: CompSci Research Topics

Algorithms & data structures
Artificial intelligence ( AI )
Computer networking
Database systems
Human-computer interaction
Information security (IS)
Software engineering
Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
An evaluation of machine learning algorithms used for recommender systems in streaming services
A review of approximation algorithm approaches for solving NP-hard problems
An analysis of parallel algorithms for high-performance computing of genomic data
The influence of data structures on optimal algorithm design and performance in Fintech
A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
A comparison of streaming algorithm performance for the detection of elephant flows
A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
Exploring the feasibility of applying information theory to feature extraction in retail datasets.
Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

Applying deep learning algorithms for speech recognition in speech-impaired children
A review of the impact of artificial intelligence on decision-making processes in stock valuation
An evaluation of reinforcement learning algorithms used in the production of video games
An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
An analysis of the ethical and social implications of artificial intelligence-based automated marking
The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
An examination of the use of artificial intelligence in orthopaedic surgery
The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

An analysis of the impact of 5G technology on internet penetration in rural Tanzania
Assessing the role of software-defined networking (SDN) in modern cloud-based computing
A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
Exploring the influence of cloud computing on security risks in fintech.
An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
An evaluation of the challenges and opportunities in 6G wireless network adoption
The role of network congestion control algorithms in improving network performance on streaming platforms
An analysis of network coding-based approaches for data security
Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Free Webinar: How To Find A Dissertation Research Topic

Topics & Ideas: Database Systems

An analysis of big data management systems and technologies used in B2B marketing
The impact of NoSQL databases on data management and analysis in smart cities
An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
Exploring the role of data warehousing and business intelligence in global consultancies
An analysis of the use of graph databases for data modelling and analysis in recommendation systems
The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
An examination of the challenges and opportunities of distributed databases in supply chain management
Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
An exploration of how artificial intelligence is changing human-computer interaction patterns in children
An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
Assessing the influence of virtual and augmented reality on consumer purchasing patterns
An examination of the use of gesture-based interfaces in architecture
Exploring the impact of ease of use in wearable technology on geriatric user
Evaluating the ramifications of gamification in the Metaverse
A systematic review of user experience (UX) design advances associated with Augmented Reality
A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Research Topic Kickstarter - Need Help Finding A Research Topic?

Topics & Ideas: Information Security

A bibliometric review of current trends in cryptography for secure communication
An analysis of secure multi-party computation protocols and their applications in cloud-based computing
An investigation of the security of blockchain technology in patient health record tracking
A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
A systematic review of secure data storage solutions used for cloud computing in the fintech industry
An analysis of intrusion detection and prevention systems used in the healthcare sector
Assessing security best practices for IoT devices in political offices
An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
A comparative study of digital signature schemes adoption in property transfers
An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

A study of agile software development methodologies and their impact on project success in pharmacology
Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
A study of the impact of DevOps practices on software development and delivery in the healthcare sector
An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
An investigation of software testing techniques and methodologies for subscription-based offerings
A review of software security practices and techniques for protecting against phishing attacks from social media
An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
Exploring the impact of software development outsourcing on project success in multinational contexts
An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

An array-based optimization framework for query processing and data analytics (Chen, 2021)
Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
Embedding constructural documentation in unit tests (Nassif, 2019)
PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
A state-based approach to context modeling and computing (Yue, 2019)
A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Research topics and ideas about data science and big data analytics

Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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EECS Celebrates Awards

EECS presents annual awards for outstanding PhD and SM theses

By [email protected].

November 6, 2018

Anne Stuart | EECS

The faculty and leadership of the Department of Electrical Engineering and Computer Science (EECS) recently presented 13 awards for outstanding student work on recent master’s and PhD theses. Awards and recipients included:

Jin-Au Kong Award for Best PhD Theses in Electrical Engineering

Yu-Hsin Chen, now Research Scientist, NVIDIA Research, for “Architecture Design for Highly Flexible and Energy-Efficient Deep Neural Network Accelerators.” Professors Vivienne Sze and Joel Emer, supervisors.
Chiraag Juvekar, now Research Scientist, Analog Garage, Analog Devices, for “Hardware and Protocols for Authentication and Secure Computation.” Professor Anantha Chandrakasan, supervisor.

George M. Sprowls Awards for Best PhD Theses in Computer Science

Arturs Backurs, now Research Assistant Professor, Toyota Technological Institute at Chicago (TTIC), for “Below P vs NP: Fine-Grained Hardness for Big Data Problems.” Professor Piotr Indyk, supervisor.
Gregory Bodwin, now Postdoctoral Researcher, Georgia Institute of Technology, for Sketching Distances in Graphs.” Professor Virginia Williams, supervisor.
Zoya Bylinskii, now Research Scientist, Adobe Research, for “Computational Perception for Multi-Modal Document Understanding.” Professor Fredo Durand and Dr. Aude Oliva, supervisors.
David Harwath, now Research Scientist, Spoken Languages Systems Group, Computer Science and Artificial Intelligence Laboratory (CSAIL), for “Learning Spoken Language Through Vision.” Dr. James R. Glass, supervisor.
Jerry Li, now VM Research Fellow, Simons Institute, University of California Berkeley, for “Principled Approaches to Robust Machine Learning Beyond.” Professor Ankur Moitra, supervisor.
Ludwig Schmidt, now Postdoctoral Researcher in Computer Science, University of California Berkeley, for “Algorithms Above the Noise Floor.” Professor Piotr Indyk, supervisor.
Adriana Schulz, now Assistant Professor, University of Washington, for “Computational Design for the Next Manufacturing Revolution.” Professor Wojciech Matusik, supervisor.

Ernst A. Guillemin Award for Best SM Thesis in Electrical Engineering

Matthew Brennan, now a PhD student in EECS at MIT, for “Reducibility and Computational Lower Bounds for Problems with Planted Sparce Structure.” Professor Guy Bresler, supervisor.
Syed Muhammad Imaduddin, now a PhD student in EECS at MIT, for “A Pseudo-Bayesian Model-Based Approach for Noninvasive Intracranial Pressure Estimation.” Professor Thomas Heldt, supervisor.

William A. Martin Award for Best SM Thesis in Computer Science

Favyen Bastani, now a PhD student in EECS at MIT, for “Robust Road Topology Extraction from Aerial Imagery.” Professors Sam Madden, Hari Balakrishnan, and Mohammad Alizadeh.
Wengong Jin, now a PhD student in EECS at MIT, for “Neural Graph Representation Learning with Application to Chemistry.” Professor Regina Barzilay, supervisor.

EECS Professor Martin Rinard and Professor Asu Ozdaglar, EECS department head, presented the awards during a luncheon ceremony. The PhD award winners were selected by Professor Dirk Englund (for electrical engineering) and Professor Vinod Vaikuntanathan (for computer science). The Sprowls Awards Committee, consisting of Professors Mohammad Alizadeh, Michael Carbin, and Julian Shun, assisted with selection of the PhD awards in computer science.

The SM awards were selected by Professor Elfar Adalsteinsson (for electrical engineering) and Professor Antonio Torralba (for computer science).

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Department of Computer Science
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Completed Doctoral Theses

Below you will find all doctoral theses that have been published on mediaTUM , TUM's publication server, since 2013.

Note: This “quick search” only finds text in the shown fields, not in abstracts or keywords. The search term must have at least 3 letters.

Ayikudi Ramachandrakumar, Balasubramanian: Computational Complexity of Verifying Parameterized Systems. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Bandle, Maximilian: Efficient Data Processing on Modern Hardware. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Biloš, Marin: Machine Learning for Irregularly-Sampled Time Series. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Charpentier, Bertrand P. A. H.: Uncertainty Estimation for Independent and Non-Independent Data. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Chen, Zhenyu: Grounding Natural Language to 3D Scenes. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Durner, Dominik: High-Performance Query Processing in the Cloud. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Farshad, Azade: Learning to Learn Neural Representations with Limited Data and Supervision. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Fent, Philipp: Low Latency Query Planning and Processing in Database Systems. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Gallersdörfer, Ulrich Simon Stefan: Public Key Infrastructures and Blockchain Systems – Utilizing Internet Public Key Infrastructures to Leverage Their Trust and Adoption in Blockchain Systems. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Heidekrüger, Stefan: Learning Continuous and Pure Bayes-Nash Equilibria in Sealed-Bid Auctions. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Huynh, Minh Tri: Acadela: A Domain-Specific Language for Modeling Executable Clinical Pathways. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Krenz, Lukas Daniel Sidney: A Fully Coupled Model for Petascale Earthquake-Tsunami and Earthquake-Sound Simulations. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Lang, Harald: Query Processing on Modern Hardware. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Lederer, Patrick: Strategic Manipulation in Social Choice Theory. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Leppin, Leonhard Andrew: Turbulence simulations of the high confinement mode pedestal in tokamak fusion experiments. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Lingg, Jakob Gerhard Peter: Shortwave-infrared Line-Scanning Confocal Microscope for Deep Tissue Imaging. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Makarov, Sergei Olegovich: Development and Implementation of a Generalized Multi-Ion Transport Model in Plasma Edge Fluid Codes. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Menhorn, Friedrich M.: Optimization under uncertainty and the multilevel Monte Carlo method. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Munilla Garrido, Gonzalo: Improving the Applicability of Differential Privacy in Data Sharing and Analytics Applications. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Rettino, Brando: Gyrokinetic investigation on linear and non-linear energetic-particle driven instabilities in experimental relevant scenarios. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Sichert, Moritz-Felipe: Efficient and Safe Integration of User-Defined Operators into Modern Database Systems. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Welzel-Mohr, Christoph: Inductive Statements for Regular Transition Systems. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Yu, Kevin: Advanced 3D UI for Immersive AR/VR Medical Teleconsultation. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
de la Rosa, Ezequiel: Machine Learning Characterization of Vascular Functions in Stroke Perfusion Imaging. Dissertation, 2024 more… BibTeX Full text (mediaTUM)
Artigues, Victor Maria Allan: Multi-Class and Cross-Tokamak Disruption Prediction using Shapelet-Based Neural Networks. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Azinović, Dejan: Inverse Rendering for Geometry and Material Reconstruction. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Bdair, Tariq Mousa Ahmad: Annotation-Efficient Medical Imaging with Deep Learning. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Bernhofer, Michael: Evolution of Transmembrane Protein Prediction. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Bullinger, Martin: Computing Desirable Outcomes in Coalition Formation. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Burwinkel, Hendrik: Deep Learning based Clinical Decision Support through Strong Differentiable Domain Priors. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Böttcher, Jan D.: Scalable Concurrency Control Methods for Modern Database Systems. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Czempiel, Tobias M.: Symphony of Time: Temporal Deep Learning for Surgical Activity Recognition. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Dendorfer, Patrick: Deep Learning for Human Motion: Advancing Trajectory Prediction and Multi-Object Tracking. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Denninger, Maximilian: Persistent Learning for Semantic Indoor Mapping in Dynamic Environments. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Eilers, Christine: Intelligent, Applicable and Acceptable Robotic Ultrasound. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Elsner, Daniel Valentin: Integrating System and Process Characteristics into Regression Test Optimization. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Engelmann, Severin Karl David: Understanding the Legitimacy of Digital Socio-Technical Classification Systems. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Fichtl, Maximilian: Algorithms for Computing Equilibria in Auctions. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Freitag, Michael Johannes: Building an HTAP Database System for Modern Hardware. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Gasteiger, Johannes: On the Convergence of Structure and Geometry in Graph Neural Networks. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Hagerer, Gerhard Johann: Opinion Mining for Qualitative Content Studies. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Hariharan, Sai Gokul: Novel Analytical and Learning-based Image Processing Techniques for Dose Reduction in Interventional X-ray Imaging. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Hauffa, Jan Lukas: Topic-Driven Characterization of Social Relationships for the Analysis of Social Influence. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Helfrich, Martin: Efficient Analysis of Population Protocols and Chemical Reaction Networks. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Isychev, Anastasia: Improving Analysis and Optimization of Finite-Precision Programs. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Khakzar, Ashkan: Rethinking Feature Attribution for Neural Network Explanation. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Kohn, André: Efficient Analytical Workflows for Computational Database Systems. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Kurle, Richard: Variational Bayes for Continual Learning and Time-Series Forecasting. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Li, Hongwei: Efficient and Cross-Domain Deep Learning for Advanced Neuroimage Analysis. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Li, Ling: Genetic investigation of coronary artery disease by Mendelian randomization and transcriptome-wide association studies. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Munjal, Bharti: Fine-grained Object Recognition with Fewer Labels: From Person Search to Few-shot Classification & Multi-object Tracking. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Palmas, Fabrizio: The Impact of Gamification on Corporate Extended Reality Training. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Petrovska, Ana: On Engineering Self-Adaptive Cyber-Physical Systems. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Prantl, Lukas: Deep Learning Methods for Simulation of Liquids. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Salpisti, Despoina: Procedural Generation of Virtual Environments as Context for Mixed Reality Experiences in the Automotive Design. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Savkin, Artem: Synthetic Data for Perception in Autonomous Driving. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Schmid, Katharina Theresia: Computational methods for design and analysis of population-based multiomics studies. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Schmidt, Tabea Ruth Jasmin: Testing the Safe Behavior of Unmanned Aerial Vehicles with Scenario-Based Testing. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Schnappinger, Markus: On Machine Learning Assisted Software Maintainability Assessments. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Seibold, Matthias Robert: Deep Learning-based Acoustic Sensing for Medical Applications. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Shugurov, Ivan: 6 DoF Pose Estimation of Known and Novel Objects With Dense Correspondences. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Swazinna, Phillip A.: Policy Regularization for Model-Based Offline Reinforcement Learning. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Thiel, Kevin Kennard: Automated Creation, Evaluation and Configuration of Markerless Object Tracking for Superimposed Augmented Reality. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Tirindelli, Maria: Physics-Inspired Machine Intelligence for Robotic Ultrasound Imaging. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Tomczak, Agnieszka Maria: Deep learning for blood cell image analysis. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Ulbl, Philipp: Collision Models for Gyrokinetic Simulations of Edge Turbulence in Fusion Plasmas. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Vestner, Matthias: Deformable Shape Correspondence Using Pointwise and Pairwise Features. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Vogel, Lukas: Adaptive Storage Structures. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Wang, Junpeng: Trajectory-based Stress Tensor Visualization and its Application in Structural Design and Optimization. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Wang, Yida: Learning-based Single View 3D Completion. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Weber, Sandro: Embodiment in Virtual and Mixed Environments. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Weil-Kennedy, Chana Yvonne Marie: Observation Petri Nets. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Wenzel, Patrick M.: Deep Learning Methods for Vehicle Localization and Control under Challenging Conditions. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Winter, Christian Michael: Managing Dynamic Workloads in Relational Database Systems. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Xie, You: Temporally Coherent Video Generation with Generative Adversarial Networks. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Yilmaz, Fatih: Application and Development of Business Capability Maps in Horizontal Collaborations. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Yu, Hao: Correspondence Estimation through Descriptor Learning for Point Cloud Registration. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Zhou, Qunjie: Deep Learning Meets Visual Localization. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Zhu, Donghao: Information Disclosure and Pricing in On-Demand Service Platforms. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
von Stumberg, Lukas Michael: Optimization- and Learning-Based Approaches to Visual SLAM and Relocalization. Dissertation, 2023 more… BibTeX Full text (mediaTUM)
Arnout, Hiba: Generative Adversarial Networks for Time Series Generation and Translation. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Avetisyan, Armen: CAD Model Retrieval and Alignment in 3D Scans. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Bayat, Amirhossein: Image Based Personalized Bone Therapy Planning using Deep Learning. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Bergmann, Paul: Unsupervised Anomaly Detection and Localization for Visual Quality Inspection. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Bernius, Jan Philip: Automatic Assessment of Textual Exercises. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Body, Thomas Alfred John: Development of Turbulence Simulations for the Edge & Divertor and Validation against Experiment. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Brunner, Julian M.: Formal Verification of Algorithms for Automata and Model Checking. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Capobianco, Nicolò: Radiotracer uptake classification using deep learning for evaluation of image-derived cancer biomarkers in PET/CT. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Chiotellis, Ioannis Nektarios: Autonomous Learning for Machine Perception. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Dhamo, Helisa: Scene Understanding and Decomposition for Synthesis and Editing. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Dürrwang, Jürgen: Steigerung der Betriebssicherheit von Personenkraftwagen durch Bedrohungsanalysen für die Informationssicherheit. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Eckl, Alexander: Online Algorithms for Scheduling with Testing. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Eder, Johannes David: Automatic Exploration of Automotive E/E Architectures. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Frerix, Thomas: From Numerical Optimization to Deep Learning and Back. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Gödel, Marion: Systematic parameter analysis to reduce uncertainty in crowd simulations. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Heinzinger, Michael: How to Speak Protein? - Representation Learning for Protein Prediction. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Janke, Maximilian M.: Online Algorithms for Scheduling and Data Management. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Jiang, Zhongliang: Intelligent Robotic Sonography: Adaptive, Dynamic and Learning-Powered Image Acquisition. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Kacianka, Severin: Accountability for Cyber-Physical Systems. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Klepper, Simon Valentin Sebastian: Continuous Research & Development – Scientific Research as Decision Support for Continuous Software Engineering in Domains with High Uncertainty. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Lehmberg, Daniel: Operator-informed machine learning: Extracting geometry and dynamics from time series data. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Linder, Oliver: Self-consistent modeling of electron runaway in tokamak disruptions. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Martin Gomez, Alejandro: Perceptual Visualization for Object Alignment in Mixed Reality. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Michels, Dominik: Development of a high-performance gyrokinetic turbulence code for the edge and scrape-off layer of magnetic confinement fusion devices. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Moin, Armin: Enabling Data Analytics and Machine Learning in Model-Driven Software Engineering of Smart IoT Services. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Pipelidis, Georgios: On Indoor Localization and Indoor Mapping – A Deeper Look into Dynamic Mapping. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Quedenfeld, Jens: Algorithms for Energy Conservation in Data Centers. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Rannabauer, Leonhard Andreas: Earthquake and Tsunami Simulation with high-order ADER-DG methods. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Reimer, Lara Marie: Physical Activity Recognition Using Mobile Devices. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Reinbold, Christian: Efficient Measures for Processing and Exploring Large-Scale Data Domains. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Samfass, Philipp: Reactive Load Balancing and Resilience Techniques in Simulation Applications on Supercomputers. Dissertation, 2022 more… BibTeX
Schmiedmayer, Paul: Designing Evolvable Web Services. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Schwarz, Gregor: Designing Large-Scale Auction Markets. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Schüle, Maximilian E.: Modern SQL for Knowledge Discovery and Dataset Versioning. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Shchur, Oleksandr: Modeling Continuous-time Event Data with Neural Temporal Point Processes. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Simson, Walter Arthur: Physics-Informed Deep Learning for Advanced Medical Ultrasound. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Soberanis Mukul, Roger David: Hybrid Convolutional and Graph-Convolutional Framework for Segmentation Refinement. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Sârbu, Paul-Cristian: Analysis and Performance Engineering for Learning with Sparse Grids. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Uludag, Ömer: Empirical Analysis of the Adoption of Large-Scale Agile Development Methods. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Vivar, Gerome: Towards Automated Clinical Diagnostic Decision Support using Machine Learning. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Wald, Johanna: 3D Scene Understanding of Static and Dynamic Indoor Environments. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Weininger, Maximilian Ph.: Solving Stochastic Games Reliably. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Weiss, Jakob Matthias: Intraoperative Visualization for OCT-Assisted Retinal Microsurgery. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Weiß, Sebastian Klaus: Deep Learning for Volume Visualization. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Zhuang, Qinyu: Non-intrusive Model Order Reduction based on Joint Space Sampling and Active Learning. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Zügner, Daniel: Adversarial Robustness of Graph Neural Networks. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
van Renen, Alexander: Persistent Memory in Database Systems. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
von Frankenberg und Ludwigsdorff, Nadine Katharina Victoria: Rationale Management for Event-Based Arbitration of Thermal Quality in Shared Spaces. Dissertation, 2022 more… BibTeX Full text (mediaTUM)
Ahmadvand, Mohsen: Strengthened, Composable, and Quantifiable Software Integrity Protection. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Ashok, Pranav: A Learning Twist on Controllers: Synthesis via Partial Exploration and Concise Representations. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Azizi Koutenaei, Bamshad: Computer-Assisted Navigation Methods for Screw Placement in Slipped Capital Femoral Epiphysis Surgery. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Baur, Christoph: Anomaly Detection in Brain MRI: From Supervised to Unsupervised Deep Learning. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Bork, Felix Jonas: Interactive Augmented Reality for Student-Centered, Explorative, and Collaborative Human Gross Anatomy Education. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Braun, Daniel: Automated Semantic Analysis, Legal Assessment, and Summarization of Standard Form Contracts. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Bui, Linda Mai: Regression Optimization for Camera Localization. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Busam, Benjamin Emanuel: High Performance Visual Pose Computation. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Duarte Pinto de Almeida Matos, Francisco: Deep Learning for Tomography, State Classification and Event Detection in Nuclear Fusion Plasmas. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Eberl, Manuel: Asymptotic Reasoning in a Proof Assistant. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Follmann, Patrick Moritz: Few-Shot Object Detection in Industrial Applications – Training Accurate Models with Few Annotations. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Gallard, Jean-Matthieu: Template-based code generation for a customizable high-performance hyperbolic PDE engine. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Golkov, Vladimir: Deep learning and variational analysis for high-dimensional and geometric biomedical data. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Haslbeck, Maximilian Paul Louis: Verified Quantitative Analysis of Imperative Algorithms. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Hauer, Florian: On Scenario-Based Testing of Automated and Autonomous Driving Systems. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Hawe, Johann Sebastian: Deciphering regulatory molecular mechanisms using graphical models. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Hou, Ji: Learning Priors from RGB-D Data for 3D Scene Understanding. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Hu, Xiaobin: Deep Learning for Medical Image Analysis. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Huth, Dominik Martin: Development of a reference process model for GDPR compliance management based on enterprise architecture. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Ibrahim, Amjad: An Actual Causality Framework for Accountable Systems. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Jadid, Adnane: Multi-IMU: Multiple Inertial Measurement Unit Systems in Mixed Reality. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Jorde, Daniel Rene: Learning from Power: Machine Learning on Electrical Signals. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Kaiser, Markus: Structured Models with Gaussian Processes. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Kazi, Anees Babasaheb: Graph Deep Learning for Healthcare Applications. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Kersten, Timo: Optimizing Relational Query Engine Architecture for Modern Hardware. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Kleehaus, Martin: Model Management along the IT Value Chain in Microservice-based IT Landscapes. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Kleinmeier, Benedikt: Modeling of Behavioral Changes in Agent-Based Simulations – Bridging the gap between social and computer science by operationalizing psychological processes. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Klushyn, Alexej: Latent Matters – Amortised Variational Inference With Constrained Optimisation and Learnable Priors. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Koschi, Markus Matthias: Set-based Prediction of Traffic Participants and its Applications to Safe Motion Planning. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Künzner, Florian: Efficient non-intrusive uncertainty quantification for large-scale simulation scenarios. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Ladewig, Leon: Online Algorithms for Packing Problems in the Random-Order Model. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Laude, Emanuel: Lower Envelopes and Lifting for Structured Nonconvex Optimization. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Littmann, Maria: Prediction of Protein Function through Machine Learning. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Littmann, Richard: Pricing in Non-Convex Markets. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Lähner, Zorah: Continuous Correspondence of Non-Rigid 3D Shapes. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Löb, Rebekka: Challenges and opportunities in PET/MR image reconstruction. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Ma, Lingni: Semantic mapping and tracking with RGB-D cameras. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Manhardt, Fabian: Towards Monocular 6D Object Pose Estimation. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Meggendorfer, Tobias: Verification of Discrete-Time Markov Decision Processes. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Mertes, Christian: Improving the genetic diagnosis of Mendelian disorders via robust outlier detection methods for transcriptome sequencing. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Meyer, Philipp Klara Johanna: Constraint-based Analysis of Distributed Systems. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Mrowca, Artur: Specification Mining in High dimensional Heterogeneous Data Sets of Large-Scale Distributed Systems. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Naik, Hemal: XR For All: Closed-loop Visual Stimulation Techniques for Human and Non-Human Animals. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Obersteiner, Michael Johannes: A Spatially Adaptive and Massively Parallel Implementation of the Fault-Tolerant Combination Technique. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Pandey, Varun: Advancing Spatial Analytical Database Systems. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Paschali, Magdalini: Learning Robust Representations for Medical Diagnosis. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Pirkl, Carolin Martha Anna: Deep Learning for Fast and Robust Multiparametric Magnetic Resonance Imaging. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Plecher, David Alexander: Impacts of Serious Games for Cultural Heritage. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Pöppl, Alexander Ludwig: Evaluation of the Actor Model for the Parallelization of Block-Structured Adaptive HPC Applications. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Qiu, Jiajun: Sequence-based prediction reveals effect of protein-, DNA- RNA-binding residues on sequence variants. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Raith, Florian Christian: Natürliche Benutzerschnittstellen im Umfeld verteilter Projektarbeit. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Salem, Aleieldin: Accurate and Reliable Labeling for Effective Detection of Android Malware. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Seckler, Steffen: Algorithm and Performance Engineering for HPC Particle Simulations. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Shahvarani, Seyedamirhesam: Parallel In-memory Data Processing using Modern Hardware. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Xu, Han: Demo Engineering: Using Software Theater for Exploratory Projects. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Yépez Mora, Vicente A.: Improving and upscaling the diagnostics of genetic diseases via gene expression and functional assays. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Zholobenko, Wladimir: Global Braginskii turbulence simulations across the edge and scrape-off layer of diverted tokamaks. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Zönnchen, Benedikt Sebastian: Efficient parallel algorithms for large-scale pedestrian simulation. Dissertation, 2021 more… BibTeX Full text (mediaTUM)
Adler, Jan: Materialized views in distributed key-value stores. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Asikin, Yonata Andrelo: Serendipity and Locality for Audio Recommendation. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Avezum, Mariana: SCOUP: A Framework for Sustainable Constraint-based Urban Planning. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Bojchevski, Aleksandar: Machine Learning on Graphs in the Presence of Noise and Adversaries. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Bytschkow, Denis: A generic hierarchic architecture for the coordination of energy management systems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Chu, Mengyu: Detail Synthesis for Fluids and Videos with Deep-Learning Algorithms. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Deng, Haowen: Learned 3D Local Features for Rigid Pose Estimation on Point Clouds. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Farcas, Ionut-Gabriel: Context-aware Model Hierarchies for Higher-dimensional Uncertainty Quantification. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Fromm, Alexander: Enhancing Data Flow Tracking for Data Usage Control. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Golagha, Mojdeh: A Framework for Failure Diagnosis. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Henze, Dominic: Dynamically Scalable Fog Architectures. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Herzog, Daniel Andreas: A User-Centered Approach to Solving the Tourist Trip Design Problem for Individuals and Groups. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Hodaie, Zardosht: ISAR: An Authoring System for lnteractive Tabletops. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Jaax, Stefan: Population Protocols: Expressiveness, Succinctness and Automatic Verification. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Kanzler, Mathias: Interactive Visualization of Large 3D Line Sets. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Karsunke, Olga: Konzept für die Entwicklung eines Echtzeit-Guidings in intermodalen Navigationssystemen (intNAV). Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Kehl, Wadim: Reconstruction and Scalable Detection and Tracking of 3D Objects. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Kern, Michael Alexander: Visualization of Coherence and Variation in Meteorological Dynamics. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Kipf, Andreas Michael: Advancing Analytical Database Systems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Kumpf, Alexander: Data-driven Ensemble Visualization. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Lahiani, Amal: Deep Learning Solutions for Cancer Drug Development in Digital Pathology. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Laina, Iro: Semantics, Language and Geometry: Learning to Understand the Scene. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Landthaler, Jörg: Improving Semantic Search in the German Legal Domain with Word Embeddings. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Lipková, Jana: Computational Modeling in Neuro-Oncology. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Löbel, Raphaela: Linear Tree Transducers – From Equivalence to Balancedness. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Mahabaleshwar, Manoj: Tool support for architectural decision making in large software intensive projects. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Maier, Robert: High-Quality 3D Reconstruction from Low-Cost RGB-D Sensors. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Maurer, Maurice: GENE-3D - a global gyrokinetic turbulence code for stellarators and perturbed tokamaks. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Mehdi, Gulnar: Semantically defined Analytics for Industrial Equipment Diagnostics. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Michel, Felix: A Collaborative Purely Meta-Model-Based Adaptive Case Management Approach for Integrated Care. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Miehle, Daniel Simon: Distributed Ledger Technologies in the Automotive Value Chain. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Möllenhoff, Thomas: Efficient Lifting Methods for Variational Problems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Müller, Alexander Christian: Proving Noninterference in Multi-Agent Systems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Ognawala, Saahil: Scalable Greybox Fuzzing for Effective Vulnerability Management. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Reeb, Jonas: Assessment of variant effect prediction. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Rippl, Michael: Parallel Algorithms for the Solution of Banded Symmetric Generalized Eigenvalue Problems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Roodaki, Hessam: Introducing Extended Reality to Ophthalmic Surgery. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Röhner, Kilian Michael: Learning from Data with Geometry-Aware Sparse Grids. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Stehle, Elias Johannes Berthold: Massively Parallel Algorithms for Data Ingestion on New Hardware. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Stotz, Hermann Wilhelm Richard: Scheduling algorithms for parallel processing and buffering problems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Taheri, Benjamin: Application of Deep Learning for Inspection in Industrial Overhaul Processes. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Tchipev, Nikola Plamenov: Algorithmic and Implementational Optimizations of Molecular Dynamics Simulations for Process Engineering. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Uphoff, Carsten: Flexible model extension and optimisation for earthquake simulations at extreme scales. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Virga, Salvatore: Multimodal Sensing for Autonomous Robotic Ultrasound Imaging. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Wimmer, Simon: Trustworthy Verification of Realtime Systems. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Zakharov, Sergey: Learning to Estimate 3D Object Pose from Synthetic Data. Dissertation, 2020 more… BibTeX Full text (mediaTUM)
Avsec, Ziga: Understanding the genome via predictive models. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Böttger-Brill, Tobias: Real-time Tracking of Objects in Image Sequences – Beyond Axis-Aligned Boxes. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Cheng, Jun: Interpreting regulatory variants with predictive models. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Depeweg, Stefan: Modeling Epistemic and Aleatoric Uncertainty with Bayesian Neural Networks and Latent Variables. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Dzvonyar, Dora: TEMPO: A Framework for Team Composition and Management in Project-Based Organizations. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Eckert, Marie-Lena Katharina Noemi: Optimization for Fluid Simulation and Reconstruction of Real-World Flow Phenomena. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Esposito, Marco: Seamless Intraoperative Robotic Imaging. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Faber, Anne Teresa Luisa: Collaborative Modeling and Visualizing of Business Ecosystems. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Gutiérrez Becker, Benjamín: Machine Learning Methods for Computer Assisted Diagnosis and Medical Image Registration. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Hazırbaş, Caner: Learning Geometry and Semantics for Deep Image Restoration. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Hein, Daniel: Interpretable Reinforcement Learning Policies by Evolutionary Computation. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Hofbauer, Johannes: Should I Stay or Should I Go? – The No-Show Paradox in Voting and Assignment. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Hupel, Lars: Verified Code Generation from Isabelle/HOL. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Johanßen, Jan Ole: Continuous User Understanding in Software Evolution. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Kahl, Matthias: Machine Learning for Non-Intrusive Load Monitoring. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Knobloch, Jan Gert: A Teaching Methodology for Massive On Campus Courses. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Kranz, Julian: Binary Analysis using On-Demand Tabulation of Function Summaries. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Kriechbaumer, Thomas: Methodologies for Distributed Acquisition and Collection of Electrical Energy Data. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Kuschk, Georg: Efficient Large-Scale Stereo Reconstruction using Variational Methods. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Mahapatra, Tanmaya: High-level Graphical Programming for Big Data Applications. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Mahlich, Yannick: Predicting functional capabilities of microbes using a similarity graph approach. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Marmsoler, Diego: Axiomatic Specification and Interactive Verification of Architectural Design Patterns in FACTum. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Merting, Sören: Mechanism Design for Combinatorial Allocation Problems without Quasilinear Utilities. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Mo-Hellenbrand, Ao: Resource-Aware and Elastic Parallel Software Development for Distributed-Memory HPC Systems. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Najafi, Mohammadreza: Hardware Accelerated Stream Processing. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Okur Kuru, Asli: Challenges in Deployment of Advanced Radioguided Surgery Solutions. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Seitz, Andreas Horst Nikolaus: An Architectural Style for Fog Computing: Formalization and Application. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Sickert, Salomon: A Unified Translation of Linear Temporal Logic to ω-Automata. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Steinbrücker, Frank Thomas: Efficient Algorithms for Large-Scale Correspondence Problems in Computer Vision. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Usenko, Vladyslav: Visual-Inertial Navigation for Autonomous Vehicles. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Wiesner, Christian A.: Increasing the maturity of the Augmented Reality Head-Up-Display. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Zec, Marin: Gestaltung von anwenderfreundlichen Gruppenunterstützungssystemen und Kollaborationsprozessen für die Problemstrukturierung und Ideengenerierung auf Grundlage der Morphologischen Analyse. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Zehetmeier, Daniela: Computer Science and Abstract Thinking – Concept, Assessment, Training. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
de Resende Ferreira, Cháulio: Vectorization and Patch-Based Adaptive Mesh Refinement for Finite Volume Solvers. Dissertation, 2019 more… BibTeX Full text (mediaTUM)
Aleatrati Khosroshahi, Pouya: Using Business Capability Maps for Application Portfolio Complexity Management. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Alkadhi, Rana Mohammed A: Rationale in Developers’ Communication. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Astfalk, Patrick: Linear and quasilinear studies of kinetic instabilities in non-Maxwellian space plasmas. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Birdal, Tolga: Geometric Methods for 3D Reconstruction from Large Point Clouds. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Brandl, Florian: Zero-Sum Games in Social Choice and Game Theory. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Cejuela Pérez, Juan Miguel: Augmenting Humans. A Text Mining Approach. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Conjeti, Sailesh: Learning to Hash for Large-Scale Medical Image Retrieval. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Doblander, Christoph: Compression in publish/subscribe systems. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Goetzendorff, Andor: Core Pricing and Spectrum Auction Design. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Habert, Séverine: Multi-Modal Visualization Paradigms for RGBD augmented X-ray Imaging. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Hackenberg, Georg: Test-driven conceptual design of cyber-physical manufacturing systems. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Haltakov, Vladimir: Learning Context For Semantic Segmentation and Applications. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Haq, Anwar Ul: Appliance Event Detection for Non-Intrusive Load Monitoring in Complex Environments. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Häusser, Philip: Learning by Association – Strategies for solving computer vision tasks with less labeled data. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Immler, Fabian: A Verified ODE Solver and Smale's 14th Problem. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Jansen, Axel: Augmented Reality in der Fahrzeugnavigation. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Ji, Shuping: Efficient Content-based Publish/Subscribe Routing and Boolean Expression Matching Algorithms. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Kraft, Dennis: Incentive Design for Present-Biased Agents – A Computational Problem in Behavioral Economics. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Miller, Carl Maximilian: Functional profiles of health: elucidating genetics and microbiome of human disease. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Milletari, Fausto: Hough Voting Strategies for Segmentation, Detection and Tracking. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Naughton, Helmut: Issue-based Model Review. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Nosovic, Stefan: FiGaRo - A Framework for Gesture-based Interface Development. Dissertation, 2018 more… BibTeX
Ralovich, Kristof: Image-based Treatment Outcome Prediction and Intervention Guidance for Cardiovascular Diseases. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Reichart, Barbara: Serious Game Patterns. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Rettenberger, Sebastian: Scalable I/O on Modern Supercomputers for Simulations on Unstructured Meshes. Dissertation, 2018 more… BibTeX
Rieke, Nicola Christin: Computer Vision-Assisted Surgery: Real-Time Instrument Tracking with Machine Learning. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Rupprecht, Christian: Learning under Ambiguity through Multiple Predictions. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Salehi, Pooya: Dependable Publish/Subscribe Systems for Distributed Application Development. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Satagopam, Venkata Pardhasaradhi: Applying data integration and knowledge management techniques to analyze systems biology data. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Schams, Sebastian: Potentials and Limitations of Contributive Social Capital Systems. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Schulze Frielinghaus, Stefan: Interprocedural Program Analysis – Herbrand Equalities and Local Solvers. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Seyyedi, Saeed: Advanced Reconstruction and Noise Reduction Techniques in Four- and Six-Dimensional X-ray Imaging Modalities. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Slavcheva, Miroslava: Signed Distance Fields for Rigid and Deformable 3D Reconstruction. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Stauder, Ralf Roland: Context Awareness for the Operating Room of the Future. Dissertation, 2018 more… BibTeX Full text ( DOI ) Full text (mediaTUM)
Steinegger, Martin: Ultrafast and sensitive sequence search and clustering methods in the era of next generation sequencing. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Stricker, Georg: Scalable longitudinal statistical models for genomics data. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Waltl, Bernhard Ernst: Semantic Analysis and Computational Modeling of Legal Documents. Dissertation, 2018 more… BibTeX Full text (mediaTUM)
Albarqouni, Shadi : Machine Learning for Biomedical Applications: From Crowdsourcing to Deep Learning. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Alperowitz, Lukas: ProCeeD – A Framework for Continuous Prototyping. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Alsheakhali, Mohamed: Machine Learning for Medical Instrument Detection and Pose Estimation in Retinal Microsurgery. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Bakhtiari, Arash: High Order Adaptive Semi-Lagrangian/Volume-Integral Methods for Parallel Advection-Diffusion Simulations. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Banescu, Sebastian-Emilian: Characterizing the Strength of Software Obfuscation Against Automated Attacks. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Barthel, Michael: Erkennung und Verfolgung von relevanten Objekten zur semantischen Annotierung von dynamischen, monokularen Szenen am Beispiel von Fußballübertragungen. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Becker, Klaus: Software Deployment Analysis for Mixed Reliability Automotive Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Bier, Philipp Christoph Sebastian: Umsetzung des datenschutzrechtlichen Auskunftsanspruchs auf Grundlage von Usage-Control und Data-Provenance-Technologien. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Brunel, Robert: Enhancing Relational Database Systems for Managing Hierarchical Data. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Dietrich, Felix: Data-Driven Surrogate Models for Dynamical Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Eckhardt, Jonas: Categorizations of Product-related Requirements in Practice – Observations and Improvements. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Engel, Jakob-Julian: Large-Scale Direct SLAM and 3D Reconstruction in Real-Time. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Femmer, Henning: Requirements Engineering Artifact Quality: Definition and Control. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Gardiazabal Schilling, José Francisco: Robotic freehand SPECT Imaging. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Hoffmann, Philipp Emanuel: Workflow Nets – Reduction Rules and Games. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Hubig, Nina: Analyzing and Predicting Large Vector-, Graph- and Spatio-Temporal Data. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Jaimez Tarifa, Mariano: Motion Estimation, 3D Reconstruction and Navigation with Range Sensors. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Jergler, Martin: Distributed Workflow Coordination in Publish/Subscribe Environments. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Knorr, Sebastian Bernhard: Leveraging the User's Face as a Known Object in Handheld Augmented Reality. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Kothmayr, Thomas: A Distributed Data Processing Perspective on Industrial Real-Time Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Langenberg, Robert: Analysis and Optimization of the Offline Software of the ATLAS Experiment at CERN. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Li, Rui: Data Mining and Machine Learning Methods for High-dimensional Patient Data in Dementia Research: Voxel Features Mining, Subgroup Discovery and Multi-view Learning. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Maurus, Samuel: Exploratory Knowledge-Mining from Complex Data Contexts in Linear Time. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Mund, Jakub Mikołaj: Measurement-based Quality Assessment of Requirements Specifications for Software-Intensive Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Narayan, Nitesh: MiNT: MULTIMODAL iNTERACTION FOR MODELING AND MODEL REFACTORING. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Neumann, René: CAVA – A Verified Model Checker. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Parra Hinojosa, Alfredo: Toward Resilient Exascale PDE Solvers Using the Combination Technique. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Peter, Loic: Automating and Assisting Image Segmentation with Decision Forests. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Pinkau, Chris: Stochastic Scheduling with Precedence Constraints. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Pöss, Meikel: Methodologies for a Comprehensive Approach to Measuring the Performance of Decision Support Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Reschenhofer, Thomas: Empowering End-users to Collaboratively Analyze Evolving Complex Linked Data. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Riesinger, Christoph: Scalable scientific computing applications for GPU-accelerated heterogeneous systems. Dissertation, 2017 more… BibTeX Full text ( DOI ) Full text (mediaTUM)
Rivera Acevedo, Jose Adan: Distributed Optimization for Electric Vehicle Charging Control. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Scheuermann, Constantin: A Metamodel for Cyber-Physical Systems. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Schwarzmayr, Thomas: Assembly and Analysis of Next-Generation Sequencing Data. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Sharma, Kanishka: Machine Learning Methods for Segmentation in Autosomal Dominant Polycystic Kidney Disease. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
Souiai, Mohamed: Convex Semantic Priors for Continuous Multi-Label Optimization. Dissertation, 2017 more… BibTeX Full text (mediaTUM)
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Holling, Dominik: Defect-based Quality Assurance with Defect Models. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
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Huang, Chun-Hao: Tracking by Detection of 3D Human Shapes in Multi-camera Environments. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
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Pankratz, Frieder: Augmented Reality for Augmented Reality. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Peters, Sebastian Matthias: MIBO – A Framework for the Integration of Multimodal Intuitive Controls in Smart Buildings. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Pölsterl, Sebastian Walter: Algorithms for Large-scale Learning from Heterogeneous Survival Data. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Resch, Christoph: Enhancing Projective Spatial Augmented Reality in Industry – A Model Based Approach for Registration and Calibration. Dissertation, 2016 more… BibTeX
Rödiger, Wolf-Steffen: Scalable Distributed Query Processing in Parallel Main-Memory Database Systems. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Sayih, Marouane: Web Engineering mit XML-Technologien. Dissertation, 2016 more… BibTeX
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Schneider, Alexander W.: Decision Support for Application Landscape Diversity Management. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Schneider, Florian: URML: Towards Visual Negotiation of Complex System Requirements. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Schulte zu Berge, Christian Ulrich: Real-time Processing for Advanced Ultrasound Visualization. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Schulze, Florian: Conversational Context for Mobile Notification Management. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Seitz, Michael J.: Simulating pedestrian dynamics – Towards natural locomotion and psychological decision making. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Steidl, Daniela: Cost-Effective Quality Assurance For Long-Lived Software Using Automated Static Analysis. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Stühmer, Jan: A Convex Optimization Framework for Connectivity Constraints in Image Segmentation and 3D Reconstruction. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Uekermann, Benjamin Walter: Partitioned Fluid-Structure Interaction on Massively Parallel Systems. Dissertation, 2016 more… BibTeX Full text ( DOI ) Full text (mediaTUM)
Unterweger, Kristof Gregor: High-Performance Coupling of Dynamically Adaptive Grids and Hyperbolic Equation Systems. Dissertation, 2016 more… BibTeX
Vetter, Christoph: Accelerated Registration and Reconstruction for Functional Nuclear Imaging. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Vicedo Jover, Maria Esmeralda: Comprehensive analysis of intrinsically disordered protein content in organisms exposed to extreme ambient conditions. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Wagner, Martin Otto Werner: Gefahrenerkennung in Konfigurationen verteilter Systeme. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Wucherer, Patrick: Simulation in medical education – A novel full-scale immersive team-based simulation environment for objective performance assessment of surgical excellence. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
Wüchner, Tobias: Behavior-based Malware Detection with Quantitative Data Flow Analysis. Dissertation, 2016 more… BibTeX Full text (mediaTUM)
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Campetelli, Alarico: An Approach for Hybrid Modelling and Formal Verification in FOCUS. Dissertation, 2015 more… BibTeX Full text (mediaTUM)
Chajdas, Matthäus Georg: A voxel-based visualization pipeline for high-resolution geometry. Dissertation, 2015 more… BibTeX Full text (mediaTUM)
Chen, Yuxiang: 3D Image Processing for Structural Analysis of Macromolecules Using Cryo-Electron Tomography. Dissertation, 2015 more… BibTeX Full text (mediaTUM)
Cheng, Xiaoyin: Improving Reconstruction of Dynamic PET Imaging by Utilizing Temporal Coherence and Pharmacokinetics. Dissertation, 2015 more… BibTeX Full text (mediaTUM)
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This page is about how to turn your research (once it's done) into a readable multi-chapter document. You need to figure out what to include, how to organize it, and how to present it.

Following this advice will make me happier about reading your submitted or draft dissertation. You may find it useful even if I'm not going to read your dissertation.

Many others have written usefully on this subject , including someone in the Annals of Improbable Research . There's also advice on writing a thesis proposal . However, this page focuses on what a finished dissertation should look like. You could also skim good dissertations on the web.

What Goes Into a Dissertation?

A typical thesis will motivate why a new idea is needed, present the cool new idea, convince the reader that it's cool and new and might apply to the reader's own problems, and evaluate how well it worked. Just like a paper!

The result must be a substantial, original contribution to scientific knowledge. It signals your official entrance into the community of scholars. Treat it as an chance to make a mark, not as a 900-page-tall memorial to your graduate student life.

Beyond stapling

The cynical view is that if you've written several related papers, you staple them together to get a dissertation. That's a good first-order approximation -- you should incorporate ideas and text from your papers. But what is it missing?

First, a thesis should cohere -- ideally, it should feel like one long paper. Second, it should provide added value: there should be people who would prefer reading it to simply reading your papers. Otherwise writing it would be a meaningless exercise.

Here's what to do after stapling:

Taking Responsibility

Don't expect your advisor to be your co-author. It's your Ph.D.: you are sole author this time and the responsibility is on your shoulders. If your prose is turgid or thoughtless, misspelled or ungrammatical, oblivious or rude to related research, you're the one who looks bad.

You can do it! Your advisor and committee are basically on your side -- they're probably willing to make suggestions about content and style -- but they are not obligated to fix problems for you. They may send your dissertation back and tell you to fix it.

In the following sections, I'll start with advice about the thesis as a whole, and work downward, eventually reaching small details such as typography and citations.

Know Your Audience

First, choose your target audience. That crucial early decision will tell you what to explain, what to emphasize, and how to phrase and organize it. Checking it with your advisor might be wise.

Pretty much everything in your thesis should be relevant to your chosen audience. Think about them as you write. Ask yourself:

What does your audience already know?

You can also safely assume that your readers have some prior familiarity with your research area. Just how much familiarity, and with which topics, is a judgment call -- again, you have to decide who your intended audience is.

In practice, your audience will be somewhat mixed. Up to a point, it is possible to please both beginners and experts -- by covering background material crisply and in the service of your own story . How does that work? As you lay out the motivation for your own work, and provide notation, you'll naturally have to discuss background concepts and related work. But don't give a generic review that someone else could have written! Discuss the background in a way that motivates and clarifies your ideas. Present your detailed perspective on the intellectual landscape and where your own work sits in it -- a fresh (even opinionated) take that keeps tying back to your main themes and will be useful for both experts and beginners.

In short, be as considerate as you can to beginners without interrupting the flow of your main argument to your established colleagues. A good rule of thumb is to write at the level of the most accessible papers in the journals or conference proceedings that you read.

What do you want your audience to learn from the thesis?

You should set clear goals here. Just like a paper or a talk, your dissertation needs a point: it should tell a story. Writing the abstract and chapter 1 at the start will help you work out what that story is.

You may find that you have to do further work to really support your chosen story: more experiments, more theorems, reading more literature, etc.

What does your audience hope to get out of the thesis?

Why does anyone crack open a dissertation, anyway? I sometimes do. Especially for areas that I know less well, a dissertation is often more accessible than shorter, denser papers. It takes a more leisurely pace, provides more explicit motivation and background, and answers more of the questions that I might have.

There are other reasons I might look at your dissertation:

For students, reading high-quality dissertations is a good way to learn an area and to see what a comprehensive treatment of a problem looks like. Noah A. Smith once ran a graduate CS seminar in which the students read 8 dissertations together. Each student was also required to select and summarize yet another dissertation and write a novel research proposal based on it.

Readers with different motivations may read your thesis in different ways. The strong convention is that it's a single document that must read well from start to finish -- your committee will read it that way. But it's worth keeping other readers in mind, too. Some will skim from start to finish. Some will read only the introductory and concluding chapters (so make sure those give a strong impression of what you've done and why it's important). Some will read a single chapter in the middle, going back for definitions as needed. Some will scan or search for what they need: a definition, example, table of results, or literature review. Some will flip through to get a general sense of your work or of how you think, reading whatever catches their eye.

High-Level Organization

Once you've chosen your target audience, you should outline the structure of the thesis. Again, the convention is that the document must read well from start to finish.

The "canonical organization" is sketched by Douglas Comer near the end of his advice . Read that: you'll probably want something like it. A few further tips:

Keep your focus

Keep your focus. Length is not a virtue unless the content is actually interesting. You do have as much space as you need, but the reader doesn't have unlimited time and neither do you.

Get to the good stuff

A newspaper, like a dissertation, is a hefty chunk of reading. So it puts the most important news on page one, and leads each article with the most important part. You should try to do the same when reasonable.

Get to the interesting ideas as soon as possible. A good strategy is to make Chapter 1 an overview of your main arguments and findings. Tell your story there in a compelling way, including a taste of your results. Refer the reader to specific sections in later chapters for the pesky details. Chapter 1 should be especially accessible (use examples): make it the one chapter that everyone should read.

Include a road map

Chapter 1 traditionally ends with a "road map" to the rest of the thesis, which rapidly summarizes what the remaining chapters or sections will contain. That's useful guidance for readers who are looking for something specific and also for those who will read the whole thesis. It also exhibits in one place what an awful lot of work you've done. Here's a detailed example .

Where to put the literature review

I recommend against writing "Chapter 2: Literature Review." Such chapters are usually boring: they're plonked down like the author's obligatory list of what he or she was "supposed" to cite. They block the reader from getting to the new ideas, and can't even be contrasted with the new ideas because those haven't been presented yet.

A better plan is to discuss related literature in conjunction with your own ideas. As you motivate and present your ideas, you'll want to refer to some related work anyway.

Each chapter might have its own related work section or sections, covering work that connects to yours in different ways.

Where to define terminology and notation

Basic terminology, concepts, and notation have to be defined somewhere. But where? You can mix the following strategies:

Retail. You can define some terms or notation individually, when the reader first needs them. Then they will be well-motivated and fresh in the reader's mind. If you use them again later, you can refer back to the section where you first defined them.

Wholesale. On the other hand, there are advantages to aggregating some of your fundamental definitions into a "Definitions" section near the start of the chapter, or a chapter near the start of the dissertation:

The downside is that such sections or chapters can seem boring and full of not-yet-motivated concepts. Unless your definitions are novel and interesting in themselves, they block the reader from getting to the new and interesting ideas. So if you write something like "Chapter 2: Preliminaries," keep it relatively concise -- the point is to get the reader oriented.

Thrift shop. Use well-known notation and terminology whenever you can, either with or without a formal definition in your thesis. The point of your thesis is not to re-invent notation or to re-present well-known material, although sometimes you may find it helpful to do so.

Make Things Easy on Your Poor Readers

Now we get down to the actual writing. A dissertation is a lot to write. But it's also an awful lot to read and digest at once! You can keep us readers turning pages and following your argument. But it's a bigger and more complicated argument than usual, so you have to be more disciplined than usual.

Break it down

Long swaths of text are like quicksand for readers (and writers!). To keep us moving without sinking, use all the devices at your disposal to break the text down into short chunks. Ironically, short chunks are more helpful in a longer document. They keep your argument tightly organized and keep the reader focused and oriented.

If a section or subsection is longer than 1 double-spaced page , consider whether you could break it down further. I'm not joking! This 1-page threshold may seem surprisingly short, but it really makes writing and reading easier. Some devices you can use:

subsectioning Split your section into subsections (or subsubsections) with meaningful titles that keep the reader oriented.

lists If you're writing a paragraph and feel like you're listing anything (e.g., advantages or disadvantages of some approach), then use an explicit bulleted list. Sometimes this might yield a list with only 2 or 3 rather long bullet points, but that's fine -- it breaks things down. ( Note: To replace the bullets with short labels, roughly as in the list you're now reading, LaTeX's itemize environment lets you write \item[my label] .)

labeled paragraphs Label a series of paragraphs within the section, as a kind of lightweight subsectioning. Your experimental design section might look like this (using the LaTeX \paragraph command):

Participants. The participants were 32 undergraduates enrolled in ... Apparatus. Each participant wore a Star Trek suit equipped with a Hasbro-brand Galactic Translator, belt model 3A ... Procedure. The subjects were seated in pairs throughout the laboratory and subjected to Vogon poetry broadcast at 3-minute intervals ... Dataset. The Vogon poetry corpus (available on request) was obtained by passing the later works of T. S. Eliot through the Systran translation system ...

footnotes Move inessential points to footnotes. If they're too long for that, you could move them into appendices or chapters near the end of the thesis. (Here's my take on footnotes .)

captions Move some discussion of figures and tables into their captions. Figures and tables should be clearly structured in the first place: e.g., graphs should have labeled axes with units. But a helpful caption provides guidance on how to interpret the figure or table and what interesting conclusions to draw from it. The figure or table should itself include helpful labels (axis

(In LaTeX, you can write \caption[short version]{long version} . The optional short version argument will be used for the "List of Tables" or "List of Figures" at the start of the thesis.)

theorems Even simple formal results can be stated as a theorem or lemma. The theorem (and proof, if included) form a nice little chunk, using the LaTeX theorem enviroment.

Breaking down equations

Long blocks of equations are even more intimidating than long swaths of text. You can break those apart, too:

Intersperse short bits of text for guidance (perhaps using LaTeX \intertext ). You might introduce line 3 of your formula with

A change of variable from x to log x now allows us to integrate by parts:

Distinguish conceptually important steps from finicky steps that just push symbols around. You can even move finicky steps to a footnote, like this:

Some algebraic manipulation 5 allows us to simplify to the following:

Use visual devices like color, boldface, underlining, boxes, or \underbrace to call attention to significant parts of a formula:

Simplify the formulas in the first place by defining intermediate quantities or adopting notational conventions (e.g., "the t subscript will be dropped when it is clear from context").

Now tie it back together

Now that you've chopped your prose into bite-sized chunks, what binds it together?

Coherent and explicit structure

Your paragraphs and chunks have to tie together into a coherent argument. Do everything you can to highlight the structure of this argument. The structure should jump out at the reader, making it possible to read straight through your text, or skim it. Else the reader will get stuck puzzling out what you meant and lose momentum.

Make sure your readers are never perplexed about the point of the paragraph they're reading. Make them want to keep turning the page because you've set up questions to which they want to know the answers. Don't make them rub their eyes in frustration or boredom and wander off to the fridge or the web browser.

So how exactly do you "highlight the structure" and "set up questions"?

Ask questions explicitly and then answer them, as I just did. This is a great device for breaking up boring prose, communicating your rhetorical goals, and making the reader think.

Explicitly refer back to previous text, as when I wrote, "So how exactly do you 'highlight the structure' and 'set up questions'?"

Use lots of transitional phrases (discourse connectives). Note that it's fine to use these across chunk boundaries; that is, feel free to start a new subsection with "For this reason, ...", picking up where the previous subsection left off.

As you come to the end of a section, remind the reader what the point was. If possible, this should lead naturally into the next section.

If a section is skippable, or chapters can be read out of order, do say so. (But don't use this as an excuse for poor organization or long distractions. Some readers tend to read straight through, and in particular, your advisor or committee may feel that they must do this.)

Lots of internal cross-references

A thesis deals with a lot of ideas at once. Readers can easily lose track. Help them out:

Each figure or table should be mentioned in the main text, so that the reader knows to go look at it. Conversely, the figure's caption may point the reader back to details in the main text (stating the section number). A caption may also refer to other figures or tables that the reader should be sure to compare.

Boldface terms that you are defining, as a textbook would. This makes the definitions easy to spot when needed. You may also want to generate an index of boldfaced terms.

Be very consistent in your terminology. Never use two terms for the same idea; never reuse one term or variable for two ideas.

Be cautious about using pronouns like "it," or other anaphors such as "this" or "this technique." With all the ideas flying around, it won't always be obvious to everyone what you're referring to. Use longer, unambiguous phrases instead, when appropriate.

Try saying "the time t " instead of just " t " or just "the time." Similarly, "the image transformation T ," "the training example x i ," etc. This style reminds the reader of which variables are connected to which concepts. You can further do this for expressions: "the total probability Σ i p i " instead of just "the total probability" or "the sum."

Feel free to lavish space where it confers extra understanding. Don't hesitate to give an example or a caveat, or repeat an earlier equation, or crisply summarize earlier work that the reader needs to understand.

Be concrete

As I read a thesis, or a long argument or construction within a thesis, I often start worrying whether I am keeping the pieces together correctly in my head. Something that has become deeply familiar and natural to you (the world expert) may be rougher going for me. If I can see some concrete demonstration of how your idea works, it helps me check and deepen my understanding.

Examples keep the reader, and you, from getting lost in a morass of abstractions. Example cases figured in your thinking; they can help the reader, too. Invented examples are okay, but using "real" examples will also show off what your methods should or can do.

Running examples greet the reader like old friends. The reader will grasp a point more quickly and completely, and remember it better, when it is applied to a familiar example rather than a new one. So if possible, devise one or two especially nice examples that you can keep revisiting to make a series of points.

Pictures serve much the same role as examples: they're concrete and they share how the ideas really look inside your head. A picture is worth at least a thousand words (= 2.5 double-spaced thesis pages).

Pseudocode is a concrete way to convey an algorithm. It is often more concise, precise, and direct than a prose description, and may be closer to your own thinking. It will also make other people much more likely to understand and adopt your methods.

Theorems , too, are concise and precise. They are also self-contained chunks, because they formally state all their assumptions. A reader sloshing through a long, complicated, contextual argument can always grab onto a theorem as an island of certainty.

Experimental results are also concrete. You don't have to wait for the experimental section: it is okay to foreshadow your experiments before you present them in full. When you are developing the theory, you can say "Indeed, we will find experimentally in section 5.6 that ..." You can even showcase an example from your experiments or give some summary statistics; these might not even show up later in the experimental section.

Commitments keep the reader anchored. As noted earlier, your dissertation should discuss alternative solutions that you rejected or are leaving to future work. That's scholarship. But make it clear from the start what you actually did and didn't do. Don't have section 2.3 chatter on about everything one could do -- that reads like a proposal, not a thesis! -- while waiting till section 4.5 or even 2.5 to reveal what you actually did.

Placing these concrete elements early is best, other things equal. Either embed them early in the section or just tell the reader early on to go look at Figure X. (If you continue the section by discussing Figure X, the reader is more likely to actually go look. Figure X or its caption can refer back to the text in turn.)

For example, consider pseudocode. Some readers prefer code to prose, and it's concise. So you may want to give pseudocode early in the section, before you ramble on about why it works. An alternative is to intersperse fragments of pseudocode with your prose explanation, as in literate programming . Of course, the pseudocode itself should also include some brief comments; where necessary these can just point to the text, as in "implements equation (5)" or "see section 3.2."

Sentences. The previous section dealt with sections and paragraphs, but how about sentences? Yours should read well. The best advice in The Elements of Style : "Omit needless words. Vigorous writing is concise." To learn how to improve your sentences, read Style: Lessons in Clarity and Grace , by Joseph M. Williams, and do the exercises. Another classic is On Writing Well , by William Zinsser.

Computers are getting exponentially faster (Moore, 1965). However, Biddle (1971) showed ...

Bandura's (1977) theory ... ... (e.g., Butcher, 1954; Baker, 1955; Candlestick-Maker, 1957, and others). The work of Minor (2001, pp. 50-75; but see also Adams, 1999; Storandt, 1997) ... According to Manning and Schütze, 1999 (henceforth M&S), ...

(Another option is the apacite package, which precisely follows the style manual of the American Psychological Association. It is nearly as flexible in its citation format, but APA style has some oddities, including lowercasing the titles of proceedings volumes. One nice thing about APA style is that if you have multiple Smiths in your bibliography, it will distinguish them where necessary, using first and middle initials. Another nice thing is the use of "&" rather than "and" in author lists; however, you can easily hack plainnat.bst to mimic this behavior.)

\usepackage[colorlinks]{ hyperref } \usepackage{ url }

\usepackage[usenames,dvipsnames,svgnames,table]{xcolor} \usepackage{soul} \newcommand{\todo}[1]{\hl{[TODO: #1]}} \todo{Either prove this or back away from the claim. I think Fermat's Last Theorem might be the key ...}

\newcommand{\todo}[1]{}

... only 58 words in the dictionary have this property. % to get that count: % perl -ne 'print if blah blah' /usr/share/dict/words | wc -l

Version control. It's probably wise to use git (or CVS or RCS or Subversion or mercurial or darcs) to keep the revision history of your dissertation files. This lets you roll back to an earlier version in case of disaster. Furthermore, if you host the repository on your cs.jhu.edu account, it will be backed up by the department.

Sharing your thesis. When you're willing to open up for comments from fellow students, your advisor, or your committee, give them a secret URL from which they can always download the latest, up-to-date release of your thesis, as well as earlier versions. (This is probably friendlier than just pointing them to your git repository.)

Keep this URL up to date with your changes. Each distinct version should bear a visible date or version number, to avoid confusion. For each new version (or on request), you should probably also supply a PDF that marks up the differences from an appropriate earlier version, using the wonderful latexdiff program (available here or as an Linux package; plays nicely with git via latexdiff-git or other scripts ) or a similar technique . (Note: If you use a makefile to build your document by running latex, gnuplot, etc., then you can also make it run latexdiff and update the URL for you.)

If you use Overleaf , just give your committee a view URL for your project. They will be able to see the PDF, visit different versions, and leave comments in the source file.

Planning Your Dissertation

Every dissertation is a little different. Talk to your advisor to draft a specific, written plan for what the thesis will contain, how it will be organized, and whom it will address. Discuss the plan with each of your committee members, who may suggest changes. They might disagree with advice on this page; find out.

As the dissertation takes shape, your plan may need some revision. Your advisor and committee may be willing to provide early feedback. But no one will want to slog through more than a version or two in detail. So ask them each how many drafts of each chapter they're willing to read, and in what state and on what schedule. Some of them nmay prefer to influence your writeup while it's still in an early, outline form. Others may prefer to wait until your prose is fairly polished and easy to read.

In addition to your advisor's goals and your committee's goals, you may have some goals of your own, e.g.,

GOOD LUCK!!! Now, download that LaTeX template , and take the first step toward filling it in today ...

Time Management

Master's in Data Science

The Data Science master's program, jointly led by the Computer Science and Statistics faculties, trains students in the rapidly growing field of data science.

Data Science lies at the intersection of statistical methodology, computational science, and a wide range of application domains. The program offers strong preparation in statistical modeling, machine learning, optimization, management and analysis of massive data sets, and data acquisition. The program focuses on topics such as reproducible data analysis, collaborative problem solving, visualization and communication, and security and ethical issues that arise in data science.

To earn the Master of Science in Data Science, students must complete 12 courses. This requires students to be on campus for at least 3 semesters (one and a half academic years). Some students will choose to extend their studies for a fourth semester to take additional courses or complete a master’s thesis research project.

SEAS will be hosting virtual information sessions this Fall for students interested in the Data Science program. Registration for these sessions is available on the Admissions Events page for prospective graduate students .

What should a graduate of the Data Science program be able to do?

The design of the program is based on eleven learning outcomes developed through discussions between the computer science and statistics faculty:

Build statistical models and understand their power and limitations

Design an experiment

Use machine learning and optimization to make decisions

Acquire, clean, and manage data

Visualize data for exploration, analysis, and communication

Collaborate within teams

Deliver reproducible data analysis

Manage and analyze massive data sets

Assemble computational pipelines to support data science from widely available tools

Conduct data science activities aware of and according to policy, privacy, security and ethical considerations

Apply problem-solving strategies to open-ended questions

Financing Your Degree

Students typically finance their master’s degree program with a combination of loans, savings, family support, grants (from governments, foundations and companies), fellowships and scholarships. We recommend you visit the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences (Harvard Griffin GSAS) Funding and Financial Aid website prior to your application to learn more about your options.

Teaching Fellowships

Approximately 15% of our students are paid Teaching Fellows, usually in the second year. TFing in the first semester is highly unusual. Teaching compensation is paid out at Harvard graduate student rates.

Master's in Data Science Leadership

In master's in data science.

How to Apply
Degree Requirements
Secondary Field in Data Science
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Harvard SEAS students Sudhan Chitgopkar, Noah Dohrmann, Stephanie Monson and Jimmy Mendez with a poster for their master's capstone projects

Master's student capstone spotlight: AI-Enabled Information Extraction for Investment Management

Extracting complicated data from long documents

Academics , AI / Machine Learning , Applied Computation , Computer Science , Industry

Harvard SEAS student Susannah Su with a poster for her master's student capstone project

Master's student capstone spotlight: AI-Assisted Frontline Negotiation

Speeding up document analysis ahead of negotiations

Academics , AI / Machine Learning , Applied Computation , Computer Science

Harvard SEAS students Samantha Nahari, Rama Edlabadkar, Vlad Ivanchuk with a poster for their computational science and engineering capstone project

Master's student capstone spotlight: A Remote Sensing Framework for Rail Incident Situational Awareness Drones

Using drones to rapidly assess disaster sites

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thesis ideas for computer science
PhD Thesis in Computer Science Image Processing

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The award for the best PhD thesis , Lisansüstü tez ödülü, جائزة أفضل أطروحة دكتوراء
From Rejected to Defended: Our Remarkable Thesis Journey
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ACM Doctoral Dissertation Award
Chelsea Finn of the University of California, Berkeley is the recipient of the 2018 ACM Doctoral Dissertation Award for her dissertation, " Learning to Learn with Gradients .". Honorable Mentions go to Ryan Beckett and Tengyu Ma, who both received PhD degrees in Computer Science from Princeton University.
Computer Science Department Dissertations Collection
Geometric Representation Learning, Luke Vilnis, Computer Science. PDF. Understanding of Visual Domains via the Lens of Natural Language, Chenyun Wu, Computer Science. PDF. Towards Practical Differentially Private Mechanism Design and Deployment, Dan Zhang, Computer Science. PDF. Audio-driven Character Animation, Yang Zhou, Computer Science
Brown CS: PhD Theses
PhD Theses. 2023 Kristo, Ani Engineering a high-performing, ... Best-first Word-lattice Parsing: Techniques for integrated syntactic language modeling (8.3 MB) • Mark Johnson ... Computer Science at Brown University Providence, Rhode Island 02912 USA Phone: 401-863-7600
Computer Science Theses and Dissertations
Theses/Dissertations from 2022. PDF. The Design and Implementation of a High-Performance Polynomial System Solver, Alexander Brandt. PDF. Defining Service Level Agreements in Serverless Computing, Mohamed Elsakhawy. PDF. Algorithms for Regular Chains of Dimension One, Juan P. Gonzalez Trochez. PDF.
MIT Theses
If you are a recent MIT graduate, your thesis will be added to DSpace within 3-6 months after your graduation date. Please email [email protected] with any questions. ... Electrical Engineering and Computer Science (2303) Civil and Environmental Engineering. (2145) Aeronautics and Astronautics. (2126) Mechanical Engineering (1792) Engineering ...
Computer Science Library Research Guide
How to search for Harvard dissertations. DASH, Digital Access to Scholarship at Harvard, is the university's central, open-access repository for the scholarly output of faculty and the broader research community at Harvard.Most Ph.D. dissertations submitted from March 2012 forward are available online in DASH.; Check HOLLIS, the Library Catalog, and refine your results by using the Advanced ...
PDF Adversarially Robust Machine Learning With Guarantees a Dissertation
A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS ... Erik Jones, Sang Michael Xie, Ananya Kumar and Evan Liu for being the best junior students to work with. They brought so much energy and enthusiasm to every meeting and taught ...
Computer Science and Engineering Theses and Dissertations
Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications, Arup Kanti Dey. PDF. AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing, Hamza Elhamdadi. PDF. Automatic Detection of Vehicles in Satellite Images for Economic Monitoring, Cole Hill. PDF
Computer Science Dissertations and Theses
Theses/Dissertations from 2019. PDF. A Secure Anti-Counterfeiting System using Near Field Communication, Public Key Cryptography, Blockchain, and Bayesian Games, Naif Saeed Alzahrani (Dissertation) PDF. Spectral Clustering for Electrical Phase Identification Using Advanced Metering Infrastructure Voltage Time Series, Logan Blakely (Thesis) PDF.
Distinguished Dissertations in Computer Science
About Distinguished Dissertations in Computer Science. The Conference of Professors of Computer Science (CPCS), in conjunction with the British Computer Society, selects annually for publication a few of the best British PhD dissertations in computer science. Its aim is to make more visible the significant British contribution to this field ...
Computer science graduates receive dissertation awards
June 15, 2021. Yuliang Li. Yuliang Li and Andrew Ross have received the second annual Computer Science Outstanding Ph.D. Dissertation Awards from the Harvard John A. Paulson School of Engineering and Applied Sciences. Li's dissertation, titled "Hardware-Software Codesign for High-Performance Cloud Networks," explores the use of emerging ...
Computer Science Graduate Projects and Theses
The Department of Computer Science is a discipline concerned with the study of computing, which includes programming, automating tasks, creating tools to enhance productivity, and the understanding of the foundations of computation. The Computer Science program provides the breadth and depth needed to succeed in this rapidly changing field. One of the more recent fields of academic study ...
Theses and Dissertations--Computer Science
Theses/Dissertations from 2024 PDF. Extracting Social Network Model Parameters from Social Science Literature, Isaac Batts. PDF. LANGUAGE MODELS FOR RARE DISEASE INFORMATION EXTRACTION: EMPIRICAL INSIGHTS AND MODEL COMPARISONS, Shashank Gupta. PDF
Computer Science Theses & Dissertations
Theses and dissertations published by graduate students in the Department of Computer Science, College of Sciences, Old Dominion University, since Fall 2016 are available in this collection. Backfiles of all dissertations (and some theses) have also been added. In late Fall 2023 or Spring 2024, all theses will be digitized and available here.
1000 Computer Science Thesis Topics and Ideas
This section offers a well-organized and extensive list of 1000 computer science thesis topics, designed to illuminate diverse pathways for academic inquiry and innovation. Whether your interest lies in the emerging trends of artificial intelligence or the practical applications of web development, this assortment spans 25 critical areas of ...
PDF Computer Science PhD Dissertation Topics
Computer Science: Ph.D. Dissertation Topics • Target Assignment and Path Planning for Navigation Tasks with Teams of Agents, P.I: Sven Koenig, Professor • A Framework for Research in Human-Agent Negotiation, P.I:Jonathan Gratch, Professor • Invariant Representation Learning for Robust and Fair Predictions, P.I:Premkumar Natarajan, Professor • Generating Psycholinguistic Norms and ...
PhD Dissertations
PhD Dissertations [All are .pdf files] Probabilistic Reinforcement Learning: Using Data to Define Desired Outcomes, and Inferring How to Get There Benjamin Eysenbach, 2023. Data-driven Decisions - An Anomaly Detection Perspective Shubhranshu Shekhar, 2023. METHODS AND APPLICATIONS OF EXPLAINABLE MACHINE LEARNING Joon Sik Kim, 2023. Applied Mathematics of the Future Kin G. Olivares, 2023
Computer Science Research Topics (+ Free Webinar)
Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you've landed on this post, chances are you're looking for a computer science-related research topic, but aren't sure where to start.Here, we'll explore a variety of CompSci & IT-related research ideas and topic thought-starters ...
EECS presents annual awards for outstanding PhD and SM theses
The faculty and leadership of the Department of Electrical Engineering and Computer Science (EECS) recently presented 13 awards for outstanding student work on recent master's and PhD theses. Awards and recipients included: Jin-Au Kong Award for Best PhD Theses in Electrical Engineering. Yu-Hsin Chen, now Research Scientist, NVIDIA Research ...
Computer Science Theses
Our research focuses on core themes of theoretical and practical computer science: artificial intelligence and symbolic computation, networked and distributed systems, systems engineering, and human computer interaction. For more information please visit the School of Computer science home page. This material is presented to ensure timely ...
Top Computer Science Ph.D. Programs
To earn a Ph.D. in computer science, each student needs a bachelor's degree and around 75 graduate credits in a computer science program, including about 20 dissertation credits. Most programs require prerequisites in computer science. A graduate with a computer science master's or graduate certificate can apply their graduate credits toward ...
Completed Doctoral Theses
2023. Artigues, Victor Maria Allan: Multi-Class and Cross-Tokamak Disruption Prediction using Shapelet-Based Neural Networks. Dissertation, 2023 more… BibTeX Full text (mediaTUM) ; Azinović, Dejan: Inverse Rendering for Geometry and Material Reconstruction. Dissertation, 2023 more… BibTeX Full text (mediaTUM) ; Bdair, Tariq Mousa Ahmad: Annotation-Efficient Medical Imaging with Deep Learning.
How to Write Up a Ph.D. Dissertation
That's scholarship. But make it clear from the start what you actually did and didn't do. Don't have section 2.3 chatter on about everything one could do -- that reads like a proposal, not a thesis! -- while waiting till section 4.5 or even 2.5 to reveal what you actually did. Placing these concrete elements early is best, other things equal ...
PhD
The thesis proposal form must be filled out, signed, and approved by all committee members. Submit the PDF form to CS PhD Student Services ([email protected] ). The thesis proposal allows students to obtain formative feedback from their reading committee that'll guide them into a successful and high-quality dissertation.
Best CompSci PhD thesis you have read? : r/compsci
Ralph Merkle's PhD thesis: "Secrecy, authentication, and public key systems" . It covers his original key exchange technique using Merkle Puzzles, digital signatures using Merkle Trees, meet-in-the-middle attack, and a lot more. Edit: I completely forgot, it also covers Merkle-Damgard Construction, which is the foundation for building (almost ...
PhD in Computer Science Dissertation Examples
The blog articulates the computer science dissertation examples which are evolving in this decade. Most of the recent Ph.D. research was conducted on Artificial Intelligence, Cybersecurity, IoT, and Cloud computing. In future decades, the world cannot survive without data. Data privacy is very vulnerable while it comes online.
Ph.D. Graduate Awarded Interdisciplinary Thesis Awards
Mehrdad Ghadiri, a recent Ph.D. graduate, was awarded the College of Computing's Outstanding Doctoral Dissertation Award and Sigma Xi's Best Ph.D. Thesis Award. Ghadiri was part of the Algorithms, Combinatorics, and Optimization (ACO) program, which he graduated from in the fall of 2023. His research interests include optimization ...
Is a PhD in Computer Science Worth It in 2024? Uncover the Pros and Cons
On average, PhD holders in computer science can earn between $92,000 and $138,000 per year. In contrast, those with a master's degree typically earn less, though still substantial salaries. According to PayScale, the average salary for a PhD holder is around $133,000, while a master's degree holder earns about $102,000 annually. Factor.
Explore an Online Ph.D. in Data Science
An online Ph.D. in data science can lead to careers in analytics, business leadership, and machine learning. The BLS projects that computer and research scientist jobs will grow 22% between 2020-2030. These professionals earned a median annual salary of $126,830 in 2020, much higher than the $41,950 for all workers.
Master's in Data Science
The Data Science master's program, jointly led by the Computer Science and Statistics faculties, trains students in the rapidly growing field of data science. Data Science lies at the intersection of statistical methodology, computational science, and a wide range of application domains. The program offers strong preparation in statistical modeling, machine learning, optimization, management ...

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Axiomatic Domain Theory in Categories of Partial Maps

The Map-Building and Exploration Strategies of a Simple Sonar-Equipped Mobile Robot

A Compositional Approach to Performance Modelling

Affine Analysis of Image Sequences

Qualified Types

Specification and Proof in Real Time CSP

Efficient Algorithms for Listing Combinatorial Structures

Logic Programming

Three-Dimensional Integrated Circuit Layout

Project Factorisations in Partial Evaluation

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A development in East Boston, Massachusetts

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A study of rotational flow in a pipe line