georgia tech math phd

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• 2021 Fall MA 4320 : Complex Analysis (MWF 11:00- 11:50AM)
• Mollene Denton CSE-Math PhD student, School of Mathematics, Georgia Tech 2019 Fall - present
• Guangyu Cui Math PhD student, School of Mathematics, Georgia Tech 2020 Fall - present
• Ho (Mark) Law CSE-Math PhD student, School of Mathematics, Georgia Tech 2020 Fall - present
• Mengyi Tang Math PhD Defense on Nov 3, 2023 School of Mathematics, Georgia Tech Thesis title: Mathematical Approaches to Identification Problems - Counting, RNA folding and PDE Identification Post-gradaute first position: Oliver Wyman Actuarial Consulting (2024-)
• Ben Ide Math PhD Defense on May 12, 2022 School of Mathematics, Georgia Tech Thesis title: A Novel Delay Differential Equation Model of the Germinal Center Reaction and an Algorithm for Minimum Length Surveillance Paths Post-gradaute first position: Xanadu (2023- )
• Haodong Sun CSE-Math PhD Defense on April 8, 2022 School of Mathematics, Georgia Tech Thesis title: Optimal Motion Planning and Computational Optimal Transport. Post-gradaute first position: Wells Fergo (2022- )
• Yuchen (Roy) He Math PhD Defense on April 9, 2021 School of Mathematics, Georgia Tech Thesis title: Mathematical and data-driven pattern representation with applications in image processing, computer graphics and infinite dimensional dynamical data mining. 2022 Sigma Xi Best Ph.D. Thesis Award , Georgia Tech Post-graduate first position: Postdoc at Shanghai Jiao Tong University, Shanghai, China Postdoc at Duke University, Durham, North Carolina (Deferred due to COVID) Current position : Tenure-track Assistant Professor at City University of Hong Kong (CityU)
• James Money PhD Defense on April 25,2006 Department of Mathematics, University of Kentucky Thesis title: Variational methods for image deblurring and discretized Picard method. post-graduate first position: Tenure-track Assist. Prof. at North Carolina Central Uni. (currently Idaho National Laboratory)
• Dr. Hao Liu Post Doc (Mentor: Prof. Wenjing Liao), 2018 Fall - 2021 Spring School of Mathematics, Georgia Tech
• Dr. Martin Huska Research fellow, University of Bologna, Italy Visiting Postdoc at Georgia Tech, Sping 2019
• Dr. Maryam Yashtini IMPACT post Doc, 2014 Fall - 2017 Spring School of Mathematics, Georgia Tech
• Dr. Seong Jun Kim Post Doc (Mentor: Prof. Haomin Zhou), 2014 Spring - 2016 Spring School of Mathematics, Georgia Tech
• J. Cui (Agnes Scott College), C. Guo (Agnes Scott College), T. Trent (Emory University), and J. Washington (Spelman College)
• 2010 Spring Undergraduate research, MA 4080 Senior Project I:Elisa Trejo
• 2010 Spring Undergraduate research, MA 2699 Research for credit: Kevin Lewis, and Trevor Siu <
• 2010 CEISMC , Teacher Professional Development Experiences Talk on July 16, 2010
• 2010 Fall Undergraduate research, MA 4090 Senior Project II: Elisa Trejo
• 2010 Fall Undergraduate research, MA 2699 Research for credit: Kevin Lewis
• 2011 Spring Undergraduate research, MA 2689, MA 2699: Kevin Lewis, and Mok, Youngtaik Kevin Lewis PURA Award President's Undergraduate Research Award, Spring 2011
• 2011 Fall Undergraduate research, MA 4080 Senior Project I: Joshua Liu
• 2012 Fall Undergraduate research, MA 4699 Undergraduate research course: Tylor Cox
• 2013 Spring Undergraduate research, MA 4699 Undergraduate research course: Tylor Cox Undergraduate Award , School of Mathematics, Spring 2013
• 2014 Spring Undergraduate research: Chenxing Wang and Lin Li
• 2015 Spring Undergraduate research: Sayem Hoque
• 2015 Fall Undergraduate research: Sayem Hoque, Kumbit Hwang. Undergradaute Advising: Chris Kwan.
• 2016 Spring Undergraduate research: Sayem Hoque, Kumbit Hwang (MA 4699), Nick Selby (MA 4699). Undergraduate Advising: Chris Kwan. Kumbit Hwang, Best Junior Undergraduate Award , School of Mathematics, Spring 2016 Nick Selby, Best Oral Presentation Award , 11th Annual Undergraduate Research Symposium. College of Science, Georgia Institute of Technology, April 19, 2016
• 2016 Summer Undergraduate research: Kumbit Hwang
• 2016 Fall Undergraduate research: Sayem Hoque, Kumbit Hwang (MA 4699), Undergraduate Advising: Chris Kwan.
• 2017 Spring Undergraduate research: Sayem Hoque, Kumbit Hwang (MA 4699), Undergraduate Advising: Chris Kwan.
• 2017 Summer Undergraduate research: Jun Xiang and Sayem Hoque
• 2018 Spring Undergraduate research: Hyunsu Park and Joshua Baker
• 2019 Fall undergraduate research: Josh Li
• 2020 Spring undergraduate research: Peiyao Wu and Yujian (Tim) Hu
• 2020 Fall undergraduate research: Peiyao Wu and Yujian (Tim) Hu
• 2021 Summer undergraduate research: Tiankuo (Hanson) Zhang
• 2021 Fall undergraduate research: Tiankuo (Hanson) Zhang and Angela Morales
• 2022 Spring undergraduate research: Tiankuo (Hanson) Zhang
• 2022 Summer undergraduate research: Bijie Liu
• 2022 Fall undergraduate research: Sanjay Srihari and Tiankuo (Hanson) Zhang
• 2023 Spring undergraduate research: Sanjay Srihari, Richard Yu and Tiankuo (Hanson) Zhang
• 2024 Fall undergraduate research: Ta'Destiny Geiger
• Yaghoub Rahimi: Math PhD student, School of Mathematics, Georgia Tech 2020 Summer - 2021 Summer (co-work)
• Gyujin Park: Math MS student, School of Mathematics, Georgia Tech 2021 Fall - 2023 Fall (Academic advisor)
• Allegra Allgeier: ML-Math MS student, School of Mathematics, Georgia Tech 2022 Summer - 2022 Fall (Reading)
• Umer Ahmed: Math PhD student, School of Mathematics, Georgia Tech 2022 Fall (Reading)
• Xuanang Li: Math PhD student, School of Mathematics, Georgia Tech 2022 Fall (Reading)
• Rundong Du: CSE-Math PhD student, School of Mathematics, Georgia Tech 2013-2018 School of Math advisor (Thesis Advisor: Prof. Park, Haesun (CSE))
• Eric Sabo: Math PhD students, School of Mathematics, Georgia Tech 2015 Fall- 2016 Spring Research and reading
• Sharika Boddie: Math PhD students, School of Mathematics, Georgia Tech 2015 Spring Advising
• Y. Wang: 2013 Fall Reading course MA 8900
• Fan Zhou: 2013 Spring Reading course MA 8900
• 2023 Spring MA 6645 : Numerical Approximation Theory
• 2022 Fall MA 4320 : Complex Analysis
• 2022 Fall MA 6701 : Math Methods of Applied Sciences I
• 2022 Spring MA 6646 : Numerical ODE (MW 9:30-10:45AM)
• 2021 Fall MA 6640 : Numerical PDE (MW 9:30-10:45PM)
• 2021 Fall MA 4320 : Complex Analysis (MWF 11:00- 11:50PM)
• 2021 Spring MA 4320 : Complex Analysis (MW 11:00- 12:15PM)
• 2020 Fall MA 4320 : Complex Analysis (MWF 11:00- 11:50AM) 2020 Fall MA 6643 : Numerical Linear Algebra (MW 12:30-1:45PM)
• 2020 Spring MA 6646 : Numerical Methods for Ordinary Differential Equations(TR 1:30-2:45PM)
• 2019 Fall MA 6640 : Introduction to Numerical Methods for Partial Differential Equation (MWF 9:05-9:50AM) 2019 Fall MA 4320 : Complex Analysis
• 2016 Fall MA 2552 : Section F, Differential Equations 2016 Fall MA 2552 : Section K, Differential Equations
• 2013 Spring MA 6645 : Numerical Approximation Theory
• 2012 Fall MA 2403 : Differential Equations (Section L) 2012 Fall MA 6640 : Introduction to Numerical Methods for Partial Differential Equation
• 2012 Spring MA 6646 : Numerical Methods for Ordinary Differential Equations
• 2011 Fall MA 2403 : Differential Equations (Section C) 2011 Fall MA 2403 : Differential Equations (Section G)
• 2011 Spring MA 6645 : Numerical Approximation Theory
• 2010 Fall MA 2413 : Differential Equations (Honors Class) 2010 Fall MA 6514 : Introduction to Methods of Applied Mathematics (Industrial Mathematics I)
• 2010 Spring MA 6646 : Numerical Methods for Ordinary Differential Equations
• 2009 Fall MA 1502 : Calculus II
• 2009 Spring MA 2403 : Differential Equations 2009 Spring MA 6645 : Numerical Approximation Theory
• 2002 Fall Undergraduate level MA 109 College Algebra
• 2002 Fall Graduate level MA 537 Numerical Analysis
• 2003 Fall Undergraduate level MA 123 Elementary Calc. and its Applications
• 2003 Fall Graduate level MA 625 Numerical Methods for Diff. Equ.
• 2004 Spring Graduate level MA 537 Numerical Analysis
• 2004 Spring Graduate level MA 611 Reading course
• 2005 Spring Undergraduate level MA 321 Introduction to Numerical Methods
• 2005 Spring Graduate level MA 537 Numerical Analysis
• 2005 Fall Undergraduate level MA 109 College Algebra
• 2005 Fall Graduate level MA 625 Numerical Methods for Diff. Equ.
• 2006 Fall Undergraduate level MA 114 Calculus II
• 2006 Fall Undergraduate level MA 321 Introduction to Numerical Methods
• 2007 Spring Undergraduate level MA 113 Calculus I
• 2007 Spring Graduate level MA 537 Numerical Analysis
• 2007 Spring Graduate level MA 611 Reading course (S.Torrealba)
• 2007 Fall Undergraduate level MA 321 Introduction to Numerical Methods
• 2007 Fall Graduate level MA 625 Numerical Methods for Diff. Equ.
• 2007 Fall Graduate level MA 611 Reading course (A. Misra)
• 2008 Spring Undergraduate level MA 321 Introduction to Numerical Methods
• 2008 Spring Undergraduate level MA 471 Advanced Calculus II

Mathematics (MATH)

MATH 0399. Support for Precalculus. 2 Credit Hours.

Practicum for Learning Support students enrolled in MATH 1113 (Precalculus).

MATH 0999. Support for College Algebra. 2 Credit Hours.

This Learning Support course provides corequisite support in mathematics for students enrolled in MATH 1111 – College Algebra. Topics will parallel topics being studied in MATH 1111 and the course will provide support for the essential quantitative skills needed to be successful in MATH 1111 . Taken with MATH 1111 , this course provides an in-depth study of the properties of algebraic, exponential and logarithmic functions as needed for calculus. Emphasis is on using algebraic and graphical techniques for solving problems involving linear, quadratic, piece-wise defined, rational, polynomial, exponential and logarithmic functions.

MATH 1111. College Algebra. 4 Credit Hours.

This course provides an in-depth study of the properties of algebraic, exponential and logarithmic functions as needed for calculus. Emphasis is on using algebraic and graphical techniques for solving problems involving linear, quadratic, piece-wise defined, rational, polynomial, exponential and logarithmic functions.

MATH 1113. Precalculus. 4 Credit Hours.

This course is an intensive study of the basic functions needed for the study of calculus. Topics include algebraic, functional, and graphical techniques for solving problems with algebraic, exponential, logarithmic, and trigonometric functions and their inverses. May only be used for degree credit with departmental approval.

MATH 11X3. Transfer Precalculus. 3 Credit Hours.

MATH 1501. Calculus I. 4 Credit Hours.

Differential calculus and basic integral calculus including the fundamental theorem of calculus. Credit not allowed for both MATH 1501 and 1712 .

MATH 1503. Calculus I for the Life Sciences. 4 Credit Hours.

Differential and basic calculus: sequences, difference equations, limits, continuity, differentiation, integration, applications. The topics parallel those of MATH 1501 with applications from life sciences.

MATH 1504. Calculus I for the Life Sciences. 4 Credit Hours.

Taylor approximations, introduction to differential equations, linear algebra, and introduction to multivariable calculus. Motivating examples drawn from life sciences.

MATH 1512. Honors Calculus II. 4 Credit Hours.

The topics covered parallel those of 1502 with a somewhat more intensive and rigorous treatment. Credit not allowed for both honors calculus and the corresponding regular calculus course. Credit not allowed for both MATH 1512 and MATH 1522. Credit not allowed for both MATH 1512 and MATH 15X2.

MATH 1550. Introduction to Differential Calculus. 3 Credit Hours.

An introduction to differential calculus including applications and the underlying theory of limits for functions and sequences. Credit not awarded for both MATH 1550 and MATH 1501 , MATH 1551 , or MATH 1503 .

MATH 1551. Differential Calculus. 2 Credit Hours.

Differential calculus including applications and the underlying theory of limits for functions and sequences. Credit not awarded for both MATH 1551 and MATH 1501 , MATH 1503 , or MATH 1550 .

MATH 1552. Integral Calculus. 4 Credit Hours.

Integral calculus: Definite and indefinite integrals, techniques of integration, improper integrals, infinite series, applications. Credit not awarded for both MATH 1552 and MATH 1502, MATH 1504 , MATH 1512 or MATH 1555 .

MATH 1553. Introduction to Linear Algebra. 2 Credit Hours.

An introduction to linear alegbra including eigenvalues and eigenvectors, applications to linear systems, least squares. Credit not awarded for both MATH 1553 and MATH 1522, MATH 1502, MATH 1504 , MATH 1512 , MATH 1554 or MATH 1564 .

MATH 1554. Linear Algebra. 4 Credit Hours.

Linear algebra eigenvalues, eigenvectors, applications to linear systems, least squares, diagnolization, quadratic forms.

MATH 1555. Calculus for Life Sciences. 4 Credit Hours.

Overview of intergral calculus, multivariable calculus, and differential equations for biological sciences. Credit not awarded for both MATH 1555 and MATH 1552 , MATH 1502, MATH 1504 , MATH 1512 or MATH 2550 .

MATH 1564. Linear Algebra with Abstract Vector Spaces. 4 Credit Hours.

This is an intensive first course in linear algebra including the theories of linear transformations and abstract vector spaces. Credit not awarded for both MATH 1564 and MATH 1553 , MATH 1554 , MATH 1522, MATH 1502, MATH 1504 or MATH 1512 .

MATH 15X1. Transfer Calculus I. 3 Credit Hours.

MATH 15X2. Transfer Calculus II. 3,4 Credit Hours.

This course includes the treatment of single variable calculus in MATH 1502. This course is not equivalent to MATH 1502. Credit not allowed for both MATH 15X2 and MATH 1502. Credit not allowed for both MATH 15X2 and MATH 1512 .

MATH 1601. Introduction to Higher Mathematics. 3 Credit Hours.

This course is designed to teach problem solving and proof writing. Mathematical subject matter is drawn from elementary number theory and geometry.

MATH 1711. Finite Mathematics. 4 Credit Hours.

Linear equations, matrices, linear programming, sets and counting, probability and statistics.

MATH 1712. Survey of Calculus. 4 Credit Hours.

Techniques of differentiation, integration, application of integration to probability and statistics, multidimensional calculus. Credit not allowed for both MATH 1712 and 1501 .

MATH 17X1. Transfer Finite Math. 3 Credit Hours.

MATH 17X2. Transfer Survey-Calc. 3 Credit Hours.

MATH 1803. Special Topics. 3 Credit Hours.

Courses on special topics of current interest in Mathematics.

MATH 1X51. Transfer Differential Calc. 2,3 Credit Hours.

MATH 1X52. Transfer Integral Calculus. 3,4 Credit Hours.

MATH 1X53. Transfer Intro Linear Algebra. 2,3 Credit Hours.

MATH 1X54. Transfer Linear Algebra. 2,3 Credit Hours.

MATH 1X55. Transfer Calculus for Life Sci. 2,3 Credit Hours.

MATH 1XXX. Mathematics Elective. 1-21 Credit Hours.

MATH 2106. Foundations of Mathematical Proof. 3 Credit Hours.

An introduction to proofs in advanced mathematics, intended as a transition to upper division courses including Abstract Algebra I and Analysis I.

MATH 2406. Abstract Vector Spaces. 3 Credit Hours.

A proof-based development of linear algebra and vector spaces, with additional topics such as multilinear algebra and group theory.

MATH 24X1. Transfer Calculus III. 3 Credit Hours.

MATH 24X3. Transfer Diff Equations. 3 Credit Hours.

MATH 2550. Introduction to Multivariable Calculus. 2 Credit Hours.

Vectors in three dimensions, curves in space, functions of several variables, partial derivatives, optimization, integration of functions of several variables. Vector Calculus not covered. Credit will not be awarded for both MATH 2550 and MATH 2605 or MATH 2401 or MATH 2551 or MATH 1555 .

MATH 2551. Multivariable Calculus. 4 Credit Hours.

Multivariable calculus: Linear approximation and Taylor's theorems, Lagrange multiples and constrained optimization, multiple integration and vector analysis including the theorems of Green, Gauss, and Stokes. Credit will not be awarded for both MATH 2551 and MATH 2401 or MATH 2411 or MATH 2561 .

MATH 2552. Differential Equations. 4 Credit Hours.

Methods for obtaining numerical and analytic solutions of elementary differential equations. Applications are also discussed with an emphasis on modeling. Credit not awarded for both MATH 2552 and MATH 2403 or MATH 2413 or MATH 2562 .

MATH 2561. Honors Multivariable Calculus. 4 Credit Hours.

The topics covered parallel those of MATH 2551 with a somewhat more intensive and rigorous treatment. Credit not awarded for both MATH 2561 and MATH 2401 or MATH 2411 or MATH 2551 .

MATH 2562. Honors Differential Equations. 4 Credit Hours.

The topics covered parallel those of MATH 2552 with a somewhat more intensive and rigorous treatment.

MATH 2603. Introduction to Discrete Mathematics. 4 Credit Hours.

Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms. Credit not awarded for both MATH 2603 and MATH 2602.

MATH 2605. Calculus III for Computer Science. 4 Credit Hours.

Topics in linear algebra and multivariate calculus and their applications in optimization and numerical methods, including curve fitting, interpolation, and numerical differentiation and integration.

MATH 2698. Undergraduate Research Assistantship. 1-12 Credit Hours.

Independent research conducted under the guidance of a faculty member.

MATH 2699. Undergraduate Research. 1-12 Credit Hours.

MATH 26X2. Transfer Linear & Disc Math. 3 Credit Hours.

MATH 26X3. Transfer Discrete Math. 3 Credit Hours.

MATH 2801. Special Topics. 1 Credit Hour.

Courses on special topics of current interest in mathematics.

MATH 2802. Special Topics. 2 Credit Hours.

MATH 2803. Special Topics. 3 Credit Hours.

MATH 2804. Special Topics. 4 Credit Hours.

MATH 2805. Special Topics. 5 Credit Hours.

MATH 2X51. Transfer Multivariable Calc. 3,4 Credit Hours.

MATH 2X52. Transfer Differential Equation. 3,4 Credit Hours.

MATH 2XXX. Mathematics Elective. 1-21 Credit Hours.

MATH 3012. Applied Combinatorics. 3 Credit Hours.

Elementary combinatorial techniques used in discrete problem solving: counting methods, solving linear recurrences, graph and network models, related algorithms, and combinatorial designs.

MATH 3012R. Applied Combinatorics Recitation. 0 Credit Hours.

Recitation for MATH 3012 .

MATH 3022. Honors Applied Combinatorics. 3 Credit Hours.

Topics are parallel to those of MATH 3012 with a more rigorous and intensive treatment. Credit is not allowed for both MATH 3012 and 3022 .

MATH 3215. Introduction to Probability and Statistics. 3 Credit Hours.

This course is a problem-oriented introduction to the basic concepts of probability and statistics, providing a foundation for applications and further study.

MATH 3225. Honors Probability and Statistics. 3 Credit Hours.

The topics covered parallel those of MATH 3215 , with a more rigorous and intensive treatment. Credit is not allowed for both MATH 3215 and 3225 .

MATH 3235. Probability Theory. 3 Credit Hours.

This course is a mathematical introduction to probability theory, covering random variables, moments, multivariable distributions, law of large numbers, central limit theorem, and large deviations. Credit not awarded for both MATH 3235 and MATH 3215 or 3225 or 3670 .

MATH 3236. Statistical Theory. 3 Credit Hours.

An introduction to theoretical statistics for students with a background in probability. A mathematical formalism for inference on experimental data will be developed. Credit not awared for both MATH 3236 and MATH 3215 or 3225 or 3670 .

MATH 3406. A Second Course in Linear Algebra. 3 Credit Hours.

This course will cover important topics in linear algebra not usually discussed in a first-semester course, featuring a mixture of theory and applications.

MATH 3670. Probability and Statistics with Applications. 3 Credit Hours.

Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance. Students cannot receive credit for both MATH 3670 and MATH 3770 or ISYE 3770 or CEE 3770 .

MATH 3801. Special Topics. 1 Credit Hour.

MATH 3802. Special Topics. 2 Credit Hours.

MATH 3803. Special Topics. 3 Credit Hours.

MATH 3804. Special Topics. 4 Credit Hours.

MATH 3805. Special Topics. 5 Credit Hours.

MATH 3XXX. Mathematics Elective. 1-21 Credit Hours.

MATH 4012. Algebraic Structures in Coding Theory. 3 Credit Hours.

Introduction to linear error correcting codes with an emphasis on the algebraic tools required, including matrices vector spaces, groups, polynomial rings, and finite fields.

MATH 4022. Introduction to Graph Theory. 3 Credit Hours.

The fundamentals of graph theory: trees, connectivity, Euler torus, Hamilton cycles, matchings, colorings, and Ramsey theory.

MATH 4032. Combinatorial Analysis. 3 Credit Hours.

Combinatorial problem-solving techniques including the use of generating functions, recurrence relations, Polya theory, combinatorial designs, Ramsey theory, matroids, and asymptotic analysis.

MATH 4080. Senior Project I. 2 Credit Hours.

The first of a two-course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.

MATH 4090. Senior Project II. 2 Credit Hours.

The second course of a two-course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.

MATH 4107. Introduction to Abstract Algebra I. 3 Credit Hours.

This course develops in the theme of "Arithmetic congruence and abstract algebraic structures". Strong emphasis on theory and proofs.

MATH 4108. Introduction to Abstract Algebra II. 3 Credit Hours.

Continuation of Abstract Algebra I, with emphasis on Galois theory, modules, polynomial fields, and the theory of linear associative algebra.

MATH 4150. Introduction to Number Theory. 3 Credit Hours.

Primes and unique factorization, congruences, Chinese remainder theorem, Diophantine equations, Diophantine approximations, quadratic reciprocity. Applications such as fast multiplication, factorization, and encryption.

MATH 4210. Mathematical Foundations of Data Science. 3 Credit Hours.

Data science methods and their mathematical foundations: linear regression, classification, and clustering, kernel methods, regression trees and ensemble methods, dimension reduction.

MATH 4221. Stochastic Processes I. 3 Credit Hours.

Simple random walk and the theory of discrete time Markov chains.

MATH 4222. Stochastic Processes II. 3 Credit Hours.

Renewal theory, Poisson processes and continuous time Markov processes, including an introduction to Brownian motion and martingales.

MATH 4255. Monte Carlo Methods. 3 Credit Hours.

Probability distributions, limit laws, and applications through the computer.

MATH 4261. Mathematical Statistics I. 3 Credit Hours.

Sampling distributions, Normal, t, chi-square, and f distributions. Moment-generating function methods, Bayesian estimation, and introduction to hypothesis testing.

MATH 4262. Mathematical Statistics II. 3 Credit Hours.

Hypothesis testing, likelihood ratio tests, nonparametric tests, bivariate and multivariate normal distributions.

MATH 4280. Introduction to Information Theory. 3 Credit Hours.

The measurement and quantification of information. These ideas are applied to the probabilistic analysis of the transmission of information over a channel along which random distortion of the message occurs.

MATH 4305. Topics in Linear Algebra. 3 Credit Hours.

Finite dimensional vector spaces, inner product spaces, least squares, linear transformations, the spectral theorem for normal transformations. Applications to convex sets, positive matrices, difference equations.

MATH 4317. Analysis I. 3 Credit Hours.

Real numbers, topology of Euclidean spaces, Cauchy sequences, completeness, continuity and compactness, uniform continuity, series of functions, Fourier series.

MATH 4318. Analysis II. 3 Credit Hours.

Differentiation of functions of one real variable, Riemann-Stieltjes integral, the derivative in Rn, and integration in Rn.

MATH 4320. Complex Analysis. 3 Credit Hours.

Topics from complex function theory, including contour integration and conformal mapping.

MATH 4347. Partial Differential Equations I. 3 Credit Hours.

Method of characteristics for first- and second-order partial differential equations, conservation laws and shocks, classification of second-order systems and applications.

MATH 4348. Partial Differential Equations II. 3 Credit Hours.

Green's functions and fundamental solutions. Potential, diffusion, and wave equations.

MATH 4431. Introductory Topology. 3 Credit Hours.

Point set topology, topological spaces and metric spaces, continuity and compactness, homotopy, and covering spaces.

MATH 4432. Introduction to Algebraic Topology. 3 Credit Hours.

Introduction to algebraic methods in topology. Includes homotopy, the fundamental group, covering spaces, simplicial complexes. Applications to fixed point theory and group theory.

MATH 4441. Differential Geometry. 3 Credit Hours.

The theory of curves, surfaces, and more generally, manifolds. Curvature, parallel transport, covariant differentiation, Gauss-Bonet theorem.

MATH 4541. Dynamics and Bifurcations I. 3 Credit Hours.

A broad introduction to the local and global behavior of nonlinear dynamical systems arising from maps and ordinary differential equations.

MATH 4542. Dynamics and Bifurcations II. 3 Credit Hours.

A continuation of Dynamics and Bifurcations I.

MATH 4580. Linear Programming. 3 Credit Hours.

A study of linear programming problems, including the simplex method, duality, and sensitivity analysis with applications to matrix games, interger programming, and networks.

MATH 4581. Classical Mathematical Methods in Engineering. 3 Credit Hours.

The Laplace transform and applications, Fourier series, boundary value problems for partial differential equations.

MATH 4640. Numerical Analysis I. 3 Credit Hours.

Introduction to numerical algorithms for some basic problems in computational mathematics. Discussion of both implementation issues and error analysis.

MATH 4641. Numerical Analysis II. 3 Credit Hours.

Introduction to the numerical solution of initial and boundary value problems in differential equations.

MATH 4695. Undergraduate Internship. 1-21 Credit Hours.

Undergraduate internship for academic credit.

MATH 4698. Undergraduate Research Assistantship. 1-12 Credit Hours.

MATH 4699. Undergraduate Research. 1-12 Credit Hours.

MATH 4755. Mathematical Biology. 3 Credit Hours.

Problems from the life sciences and the mathematical methods for solving them are presented. The underlying biological and mathematical principles and the interrelationships are emphasized. Crosslisted with BIOL 4755.

MATH 4777. Vector and Parallel Scientific Computation. 3 Credit Hours.

Scientific computational algorithms on vector and parallel computers. Speed-up and algorithm complexity, interprocesses communication, synchronization, modern algorithms for linear systems, programming techniques, code optimization. Crosslisted with CS 4777.

MATH 4782. Quantum Information and Quantum Computing. 3 Credit Hours.

Introduction to quantum computing and quantum information theory, formalism of quantum mechanics, quantum gates, algorithms, measurements, coding, and information. Physical realizations and experiments. Crosslisted with PHYS 4782 .

MATH 4801. Special Topics. 1 Credit Hour.

MATH 4802. Special Topics. 2 Credit Hours.

MATH 4803. Special Topics. 3 Credit Hours.

MATH 4804. Special Topics. 4 Credit Hours.

MATH 4805. Special Topics. 5 Credit Hours.

MATH 4873. Special Topics. 3 Credit Hours.

This course enables the school of Mathematics to comply with requests for courses in selected topics.

MATH 4999. Reading or Research. 1-21 Credit Hours.

Reading or research in topics of current interest.

MATH 4XXX. Mathematics Elective. 1-21 Credit Hours.

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Doctoral Degrees

Industrial engineering (phd), college of computing, algorithms, combinatorics, and optimization (ph.d.), computational science and engineering (ph.d.), computer science (ph.d.), human-centered computing (ph.d.), machine learning (ph.d.), college of design, architecture (ph.d.), building construction (ph.d.), city and regional planning (ph.d.), music technology (ph.d.), college of engineering, aerospace engineering (ph.d.), biomedical engineering (ph.d.), chemical engineering (ph.d.), civil engineering (ph.d.), electrical and computer engineering (ph.d.), engineering science and mechanics (ph.d.), environmental engineering (ph.d.), materials science and engineering (ph.d.), mechanical engineering (ph.d.), nuclear engineering – medical physics option (ph.d.), nuclear engineering – nuclear enterprise management option (ph.d.), nuclear engineering (ph.d.), operations research (ph.d.), robotics (ph.d.), college of sciences, applied physiology (ph.d.), bioengineering (ph.d.), bioinformatics (ph.d.), biology (ph.d.), chemistry (ph.d.), earth and atmospheric sciences (ph.d.), mathematics (ph.d.), ocean science and engineering (ph.d.), physics (ph.d.), psychology (ph.d.), quantitative biosciences (ph.d.), ivan allen college of liberal arts, digital media (ph.d.), economics (ph.d.), history and sociology of technology and science (ph.d.), international affairs, science, and technology (ph.d.), public policy (ph.d.), scheller college of business, management (ph.d.).

H. Milton Stewart School of Industrial and Systems Engineering

College of engineering, ph.d. in operations research.

The core strength comprising the discipline of Operations Research (OR) at Georgia Tech resides in the Stewart School of Industrial and Systems Engineering (ISyE). One of the largest programs in the country, approximately half of the entire ISyE faculty is directly responsible for the OR program through teaching and research activities that span virtually every topic and sub-discipline related to the field's basic methodologies of optimization, stochastics/applied probability and simulation. Most important, the OR faculty in the School currently counts among its members some of the most important figures in their respective concentrations, also making the program one of the strongest anywhere.

Students pursuing a degree in Operations Research (OR) are exposed to a host of research activities in the School. As one would expect from a program as large as ours, the range and depth of these activities are substantial. Depending upon your taste, your background, or your career intentions, you can engage in research that spans from the most fundamental/theoretical to work that places greater emphasis on applications. No matter your inclination, as an OR student, you can generally find several faculty doing work in your chosen concentration.

Students are attracted to our OR degree from a variety of academic disciplines and specializations. Most prominent are applicants from mathematics/mathematical sciences, theoretical computer science, and various engineering majors such as electrical and industrial engineering. However, it is not uncommon to also find qualified students from fields such as physics, economics, and statistics.

New Ph.D. students are admitted for each Fall semester only, and the admissions process is coordinated by the Associate Chair for Graduate Studies. Decisions on applicants to our various Ph.D. programs are determined jointly by a committee of faculty members, potential faculty research advisors, and the Associate Chair. All applicants must select and apply to a specific degree program, although it is possible in some cases to switch programs after enrollment.

A prior Master's degree is not a requirement for admission into our Ph.D. programs, and students can earn an M.S. degree typically within the first two years of Ph.D. study. For those unsure about applying to a Master's program versus a Ph.D. program, please note that students in our Master's programs are not guaranteed admission into a Ph.D. program here; we do offer a simplified application scheme. If you are interested in research and a Ph.D. degree, you should apply to a Ph.D. program directly.

Application Requirements

• Transcripts : Transcripts of prior academic work are required, as is evidence of an earned Bachelor's degree. Applicant transcripts should demonstrate strong academic preparation and capability, especially in advanced mathematics and computing coursework. Those with less preparation in mathematics and engineering are expected to use coursework at Georgia Tech to quickly establish proficiency. 
• Graduate Record Examination (GRE) : Scores from the general test are required, and strong performance on the quantitative section is expected. Scores from the Mathematics Subject Test are not required, but can help a student demonstrate proficiency in advanced mathematics.  **The GRE is optional for the 2024 admissions cycle for Ph.D. applicants.**   However, if you decide not to submit GRE scores, the rest of your academic record should make up for the lack of the test score. If you have GRE test scores and wish to submit them for Fall 2023, they will be accepted and considered.  
• Statement of Purpose : The written statement of purpose should describe clearly why the applicant wishes to pursue the Ph.D., including research and career goals. While the statement should describe past experiences, it should also identify clearly the research area of interest to the applicant and the members of our faculty that might serve as research advisor(s).
• Resume: A resume outlining academic experience, research experience and accomplishments, industry experience, specific skills, and outside interests of the applicant is required.
• Letters of Reference:   Three (3) credible letters of reference are required that attest to the preparation of the applicant and the likelihood for success in a Ph.D. program. At least two (2) letters should be from faculty members.  

Each year, we receive many more applications from qualified students than we have the capacity to admit into our programs. To help admitted students learn more about our programs and meet potential research advisors, we hold an invitation-only Ph.D. Applicant Visit Day annually in early March.  

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Career Paths

ISyE produces well-rounded graduates who go on to make an extraordinary mark on the world through their leadership in engineering and technology. With broad skill sets and innovative minds molded by the number one school of industrial engineering in the country, our graduates are out changing the world and paving the way for future generations..

A sample of companies our Ph.D. graduates launched their careers with

• BHP Billiton
• Norfolk Southern
• Descartes Associates
• GE Global Research
• JP Morgan Chase
• Suntrust Bank
• Delta Technologies
• Capital One
• United Airlines

A sample of academic institutions our Ph.D. graduates launched their careers with

• MIT (Sloan/ORC)
• Carnegie Mellon (Business, Statistics)
• Purdue (Industrial Engineering)
• Harvard (Statistics)
• Iowa (Business)
• Arkansas (Industrial Engineering)
• Texas-Austin (Operations Research)
• Northwestern (IEMS, Business)
• Lehigh (Industrial Engineering)
• Florida (Industrial Engineering)
• North Carolina-Chapel Hill (Operations Research, Business)
• Middle East Technical University [Turkey] (Industrial Engineering)
• Duke (Business)
• Chicago (Business)
• Minnesota (Industrial Engineering)
• University of Chile (Industrial Engineering)
• Texas A&M (Industrial Engineering)
• Virginia Tech (Industrial Engineering)

Prospective Student Resources

New student checklist, graduate orientation resources, graduate handbook, financial aid.

Yes, the IELTS exam is accepted. See here for score requirements:  https://www.grad.gatech.edu/english-proficiency  

Transfer credit is accepted only in rare cases, and must be approved by the Associate Chair of Graduate Studies, ISyE. The review and approval process typically takes place during a student’s first semester in the program. A maximum of six total credit hours are transferrable. 

You may begin your application here: http://www.grad.gatech.edu/apply-now

Applicants should track their status through the CollegeNet online status check found here: https://www.grad.gatech.edu/status-checking

All ISyE Ph.D. students receive some type of funding and this is typically via a graduate assistantship (GRA or GTA). Sometimes students are supported by external fellowships. Please see here for more information on support: https://www.isye.gatech.edu/academics/doctoral/current-students/financial-support  

It is common for Ph.D. students to earn a Master’s degree as they progress through their Ph.D. program of study. That is, appropriate courses taken as part of their Ph.D. program are often applied to satisfy relevant degree requirements for a single Master’s degree. The review and approval process must go through the Associate chair for Graduate Studies.  Ph.D. students will not however be granted multiple Master’s degrees from ISyE. 

No. All Ph.D. students studying in ISyE receive financial support in the form of a graduate assistantship. There is no separate application required.  https://www.isye.gatech.edu/academics/doctoral/prospective-students/financial-support

Yes. ISyE Ph.D. students must be enrolled in the Atlanta campus.

Exceptions are given to applicants from countries where English is the SOLE OFFICIAL language of instruction. An applicant is also exempt if they have studied for at least one academic year at a U.S. college or university. Please visit https://grad.gatech.edu/english-proficiency for further information on the English Proficiency requirements for international students.

Applicants are required to submit a Statement of Purpose describing his or her motivation for pursuing the Ph.D. in ISyE, including a description of current research interests. Additionally, all applicants are required to submit transcripts of prior academic coursework, official GRE exam scores, and three recommendation letters.  

Please review the Georgia Tech English Proficiency Requirements here: https://grad.gatech.edu/english-proficiency .

The best preparation for a Ph.D. in Industrial Engineering or Operations Research at Georgia Tech is a technical program in mathematics, industrial engineering, operations research, statistics, or computer science. Students are expected to have strong understanding of calculus, applied probability, statistics, linear algebra, and computing. Also desirable are proof-based mathematics courses.  

Please see our admissions page here for additional information:  https://www.isye.gatech.edu/academics/doctoral/phd-industrial-engineering/admissions

The application deadline for our Ph.D. program is December 15. We offer fall admission only and classes begin in August.

Copies of your transcripts should be uploaded with your online application. If you are admitted to the program and decide to enroll, you will be required to have official transcripts sent to the Office of Graduate Studies.

Graduate Studies Georgia Institute of Technology 631 Cherry St., Room 318 Atlanta, GA 30332-0321

Our goal is to have all Ph.D. applications reviewed and official admissions decisions out by the end of February. 

Please refer to our ISyE Graduate Handbook .

Please visit our website for information related to: Admissions, Curriculum, Specializations, Financial Support, Research Faculty, Placement, etc.  https://www.isye.gatech.edu/academics/doctoral/industrial-engineering

Academic recommendations are strongly preferred. We require a total of three and they should be very strong. 

Academic recommendation letters are strongly preferred.  We ask for three letters of recommendations and they should be very strong.    

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Georgia tech mathematics and applications portal.

GT MAP is a place for research discussion and collaboration. We welcome participation of any researcher interested in discussing his/her project and exchange ideas with Mathematicians. Mathematics can provide useful tools and insights to different research projects, and  GT-MAP is to provide a channel of various discussions.

Feel free to consider giving presentations in our seminar series and workshop, or just walk on over to the Math department on Friday afternoon for seminars, or to discuss, or just for a coffee/tea.

PostDoc Position Announcement October 2018

We expect to sponsor one post-doctoral position, housed in the School of Mathematics, starting in Fall 2019. This is a two year position and is intended for recent PhDs in Applied Mathematics, with demonstrated evidence or potential to carry out research of the highest quality, and have a commitment to high quality teaching.  Ability to collaborate with other units across Campus is a definite plus.  Interested applicants should do so via Mathjob.org and indicate the "GT MAP post-doctoral position" in their cover letter.

Please join our GT-MAP mailing list here .

If you are interested, here is a link to School of Mathematics weekly Seminars and Colloquia .

--------------------------------------------------------------

First launching seminar by Prof. Magnus Egerstedt (GT ECE) February 5, 2016

The first GT MAP Workshop on Materials, August 17- 19, 2016.   

 Working Group for Problems in Transport and Related Topics in Graphs, May 9-10, 2017.

 Workshop on Dynamical Systems, Aug 10-11, 2017

The second GT MAP Workshop on Dynamics and Control, August 17-18, 2017

Mini-Workshop on Mathematics and Dynamical Systems, December 1, 2017

Mini-Workshop on Mathematics, Dynamics and Control, April 13, 2018

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School of Biological Sciences

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Ph.d. biology.

Our PhD program accepts students possessing Bachelors or Masters degrees who are planning a career in science. The purpose of our PhD program is to prepare highly qualified scientists who have excellent up-to-date training in the fields of biology or bioinformatics, who are actively involved in scientific research, are capable of making significant contributions to their scientific field, possess all the necessary skills for effective oral and written communication with colleagues, and can successfully compete in the job market for postdoctoral and research scientist level positions in academia and science-related industries.

We currently have approximately 100 PhD students in the Biology PhD program of the School of Biological Sciences. Of recent PhD graduates, 70% are currently employed as postdoctoral researchers in academia, 9% as government scientists , 9% as industry scientists , 4% as instructors , and 9% are enrolled in further professional training . The average number of journal publications is 3.9 per student and the average number of presentations at conferences around the world is 4.3 per student .

Areas of concentration:

• Ecology, Evolution, and Behavior   including population and evolutionary ecology; community ecology; aquatic chemical ecology; ecological genomics; sensory ecology; evolution of development, behavior, and sociality; biological oceanography; environmental microbiology; theoretical ecology.
• Molecular and Cell Biology   including eukaryotic and prokaryotic cell biology; molecular physiology; molecular biophysics and structural biology; animal, plant, and microbial molecular genetics; human genomics; molecular evolution.

Quick Facts

• Stipend and tuition waiver offered.
• Fellowships available.
• Duration of program depends on research progress. Ph.D. candidates typically defend their thesis at the end of the 5th or during the 6th year.
• 18 credit hours of coursework.

General Inquiries

• Chung Kim Academic Program Coordinator Email  | 404.385.4240 | EBB 2009

Ph.D. Program Overview:

• Stipend: $35,500 per year
• Year 1 Focus:  Coursework / Lab Rotations / Teach
• Year 2 Focus:  Coursework / Thesis Research / Qualifying Exams
• Year 3 Focus:  Thesis Research
• Year 4 Focus:  Thesis Research
• Year 5 Focus:  Thesis Research, Writing and Defense

The PhD in Biology is a research-based degree involving deep immersion in a topic within biology with mentoring from an advisor and thesis committee with expertise in the field of study. Coursework is typically completed within the first 2 years (18 credit hours). Students who have previously earned an M.S. degree or taken graduate courses elsewhere can negotiate up to 9 transfer credit hours upon entering our program. Selection of a thesis advisor is made in discussion with our faculty and/or via lab rotations during the first year, and the composition of the thesis committee is established by the student by the end of the first year.

PhD students in the School of Biological Sciences are each supported by a stipend and do not pay tuition, only modest   fees   each semester. Stipend support comes from teaching or research assistantships which complement research training towards the PhD. Whether PhD stipends are earned from research or teaching assistantships after the first year is decided in consultation with a student's thesis advisor and the graduate committee. Our base PhD stipend is $35,500. Several fellowships are available which can supplement the PhD stipend.

Further Funding

Please take some time to review our   funding opportunities and fellowships .

Choosing between the Masters and Ph.D. Program

Our graduate program is primarily focused on the PhD which prepares students for careers in scientific research and employment in academia, industry, or government. We encourage potential applicants to the PhD program to directly contact individual   faculty   members whose research may appeal to them to discuss research interests and future opportunities. Students who are not yet sure of their interest in scientific research or are interested in other kinds of professional development should consider the M.S. degree in   Biology   or  Bioinformatics . Admission decisions are made by our graduate committee (composed of Biology faculty) in consultation with all of the faculty in the School of Biological Sciences.

Georgia Tech provides application fee waivers to advance diversity, recognize outstanding undergraduate achievement, and engage prospective students in recruitment events where Georgia Tech is affiliated. Such fee waivers are currently available only to domestic applicants.

Georgia Tech Resources

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• Campus Visits
• Directions to Campus
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• Barnes & Noble at Georgia Tech
• Ferst Center for the Arts
• Robert C. Williams Paper Museum

College of Sciences Social Links

Biology related research centers.

• Aquatic Chemical Ecology Center
• Center for Biologically Inspired Design
• Center for Integrative Genomics
• Center for NanoMAD
• Center for Ribosomal Evolution and Adaptation
• Center for the Study of Systems Biology
• Integrated Cancer Research Center

Georgia Institute of Technology School of Biological Sciences 950 Atlantic Drive Atlanta, GA 30332 Office: 404-894-3700 Fax: 404-894-0519

Georgia Institute of Technology North Avenue, Atlanta, GA 30332 404.894.2000

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Graduate Education

Office of graduate and postdoctoral education, fellowships and funding.

Georgia Tech awards and coordinates numerous student fellowships – varying in value from a few hundred dollars that may be awarded on top of other funding such as an assistantship, to full fellowships that cover tuition, fees and pay a stipend.

Institute-level fellowships are managed by the Office of Graduate Education and paid via the Office of Scholarships & Financial Aid and the Office of the Bursar . Most fellowships are awarded and nominated internally by schools, not by Graduate Education nor the Office of Scholarships and Financial Aid. There are also many school-level fellowships which are handled separately by individual academic departments.

The Office of Graduate Education administers Institute-funded fellowships such as the President’s Fellowship  and the Georgia Tech Institute Fellowship , and many others. For example, we manage externally funded programs such as the National Science Foundation’s Graduate Research Fellowship Program, Ford Foundation and Department of Energy fellowships. We work with colleges to facilitate internal competitions for ARCS Foundation Atlanta scholars, and nomination processes for Dolores Zohrab Liebmann , Gilliam fellowship for Advanced Study and Schmidt Science Fellows. We also work with Academic Deans from individual Colleges to facilitate selection processes for donor-initiated fellowships.

The following information is meant to help you better understand the fellowship and funding opportunities available to you.

Fellowships vs. Scholarships

Fellowships:.

• Usually awarded for doctoral research.
• Merit-based; not need-based.
• Funding is typically meant to be used for tuition and fees but is sometimes discretionary for student awardees to use as they see fit.
• Often come with a stipend.

Scholarships:

• Awarded to students based on academic achievements, financial need, or a combination of both.
• Usually merit-based; sometimes need-based.
• Generally, funding must be applied directly to tuition and other related expenses.
• Do not include stipends.

Fellowship Opportunities

There are a variety of fellowship opportunities available to graduate students. The awards listed in this section are only a selection of those available.

Unless otherwise noted, many of the awards listed in this section are open only to U.S. citizens and/or U.S. residents. It is challenging for international students to secure fellowships because many are funded by the U.S. government and/or come with a U.S. citizenship requirement.

Be sure to search online utilizing the resources and databases below and ask professionals in your field for additional options.

NSF GRFP Applicants and Awardees

If you are interested in applying for the National Science Foundation Graduate Research Fellowship Program (NSF GRFP) or if you have already received this fellowship, please consult the following:

• Guidance for Those Applying to the NSF Graduate Research Fellowship Program (PDF)
• NSF GRFP Eligibility Quiz

Important Information for All NSF GRFP Fellows (New and Current) (PDF) ( This document was last updated April 29, 2024; if your version doesn't show this date, clear browsing history and refresh to receive the most up-to-date information.)

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Fellowships Databases

Most fellowships are largely tied to doctoral research, and many are heavily focused on STEM disciplines. There are more limited fellowship and funding options for master’s level students and programs. If you are a master’s level student, or are considering a master’s level program, you may be more likely to secure a fellowship if you are pursuing a research-based master’s degree.

We recommend students to explore fellowship opportunities available for a wide range of degree levels, disciplines, program types, etc., by accessing the fellowship databases below.

Peer Institution Fellowship Databases

Peer institutions offer fellowship databases which students can use to filter by your circumstances and interests. Please disregard those opportunities that are specific to enrollment at those universities.

• University of Illinois at Urbana-Champaign
• University of Chicago
• University of California-Los Angeles (UCLA) GRAPES Database
• University of Pennsylvania
• Duke University Research Funding Database
• Johns Hopkins University

Other External Fellowship Databases

• The U.S. National Science Foundation supports research opportunities and provides stipends for graduate students and postdoctoral fellows and scholars.
• There are multiple ways to find these programs, including the  funding search  on NSF’s website and the  NSF Education & Training Application , which is growing its list of opportunities for graduate students and postdoctoral scholars.
• Opportunities for all disciplines and project types.
• Create an account to save searches and receive funding alerts. View instructions on how to create an account .
• Georgia Tech Library regularly offers workshops on how to use Pivot effectively. Keep an eye out for the next workshop on the Library events page.
• Opportunities aimed at increasing diversity and underrepresented minority representation.
• Research internships, fellowships, and scholarships funded by the government and private sector organizations.

Fellowship Announcements

• Many fellowships are internally selected or nominated by a student’s faculty advisor or department.
• Graduate Education will circulate announcements to specific academic units, entire colleges, or campuswide.
• Some competitions will be listed within Georgia Tech’s InfoReady Review platform.
• Other announcements will first be circulated to the Graduate Coordinator’s email distribution list and then forwarded to students, as applicable.
• Students are also notified of funding opportunities via announcements in the biweekly GradBuzz e-newsletter that goes out to all currently enrolled graduate students.

Preparing Fellowship Applications

• Once you begin the fellowship application process, the Communication Center is a great resource.
• Contact the Pre-Graduate and Pre-Professional Advising unit for help with locating additional fellowship opportunities and preparing applications.
• See the Fellowships Writing Resources Dropbox folder (GT login required) for workshop recordings, presentation slides, and more resources from the Georgia Tech Director of Professional Development and Postdoctoral Services.

Fellowship and Scholarship Resources

General scholarships.

• Scholarships.com: Graduate Scholarships
• Open Education Database: Graduate Scholarships
• Smart Scholar

Student-Specific Scholarships

• International Scholarships Search
• Scholarship Guide for Black Students
• Best Colleges: Scholarships for Women

Tax Resources for Fellowships

Georgia Tech is unable to provide tax, financial or advice, and therefore all questions regarding taxes should be directed to a tax or financial advisor. The website " Personal Finance for PhDs " may be useful.

Do I include my scholarship, fellowship, or education grant as income on my tax return (for U.S. citizens and residents for tax purposes ONLY)?

This IRS Interactive Tax Assistant will help you determine whether the educational assistance you received is taxable. If you attended more than one educational institution and the funds were used for expenses other than qualified education expenses, run the interview separately for each educational institution.

Is my fellowship taxable if I am a nonresident for tax purposes?

In general, U.S. sourced taxable scholarships, fellowships, and grants that do not represent compensation for services are not subject to withholding when paid to U.S. citizens and residents, but they are subject to withholding when paid to nonresident aliens. If you are not sure if you are a resident or nonresident for tax purposes be sure to consult your GLACIER account. If you do not have a GLACIER account, please put in a ticket at asc.gatech.edu for assistance.

The withholding tax rate for nonresidents for tax purposes is 30%. However, the withholding tax rate may be reduced to 14% (or a lower treaty rate) if you are a nonresident alien student, researcher, or grantee who is temporarily present in the United States with an "F," "J," "M," or "Q" visa, and the taxable amounts you received are either:

• Incident to a qualified scholarship to which section 117(a) applies; or
• Granted by certain types of organizations described in section 1441(b)(2).

If, immediately before arriving in the United States, you were a tax resident of a country that has an income tax treaty with the United States, then you may be eligible for benefits under the applicable treaty, such as an exemption from tax, with respect to your scholarship, fellowship, or grant, including a specified amount that represents compensation for services. In order to determine whether you are eligible for a tax treaty, please consult your GLACIER account. If you do not have a GLACIER account, please put in a ticket at asc.gatech.edu for assistance.

Any part of your scholarship, fellowship, or grant that represents compensation for services performed in the United States is subject to graduated withholding.

Additional Resources

• Office of Scholarships and Financial Aid | Tax Information
• IRS | Tax Benefits for Education
• IRS | Tax Information for Individuals
• IRS | Tax Witholding Estimator
• How Fellows Should Prepare for Tax Time at the Start of the Academic Year | Inside Higher Ed
• Foreign Students, Scholars, Teachers, Researchers, and Exchange Visitors

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Ph.d. graduate earns 2024 w.s. moore young investigator award.

Retta El Sayed (left) accepts the 2024 W.S. Moore Young Investigator’s Award by the International Society for Magnetic Resonance in Medicine (ISMRM).

  By Yanet Chernet

Retta El Sayed, a Ph.D graduate from Georgia Tech and Emory University’s Wallace H. Coulter Department of Biomedical Engineering, was awarded the 2024 W.S. Moore Young Investigator’s Award by the International Society for Magnetic Resonance in Medicine (ISMRM). Sayed received this recognition for her research titled, “Assessment of Complex Flow Patterns in Patients with Carotid Webs, Patients with Carotid Atherosclerosis & Health Subjects using 4D Flow MRI.”

“Being awarded the W.S. Moore Young Investigator Award is a tremendous honor that validates the effort and commitment I've dedicated to my research,” El Sayed said. “It's humbling to be recognized among such talented peers in the field and the ISMRM community.” 

ISMRM’s W.S. Moore Award, the second major award given at the Young Investigator Award competition, celebrates the best clinical science paper published in the Journal of Magnetic Resonance Imagining (JMRI). El Sayed focused her research on cardiovascular disease as a part of her Ph.D. dissertation.

Her research investigates how magnetic resonance imaging (MRI) can offer precise patient-specific diagnoses. Specifically, El Sayed investigates the complex blood flow patterns in patients with Carotid Webs (CaW), a form of fibromuscular dysplasia (FMD), known to increase the risk of strokes, especially in young African American women.

El Sayed was one of three Young Investigators Award winners.

What sets her research apart is that it's the first study to utilize 4D flow MRI to examine complex hemodynamics linked to CaW, comparing them to patients with atherosclerosis and normal subjects.

“My research is important as it represents one of the early studies investigating hemodynamics in subjects with CaW,” said El Sayed. “This award motivates me to continue pushing boundaries and making meaningful contributions aiming to advance cardiovascular imaging and its clinical applications.”

Her research has the potential to revolutionize the way patients with carotid artery disease are diagnosed and treated, paving the way for more personalized medical interventions, including predicting surgical outcomes.

For El Sayed, the journey is far from over. Next, she’ll be developing a stroke risk assessment tool to guide clinical decision-making, particularly for patients with incidental findings of CaW.

“I am committed to leveraging and enhancing my engineering skill set to explore and address other clinical challenges encountered by the scientific and medical communities in the realm of cardiovascular MRI research,” said El Sayed.

Kelly Petty   Communications Wallace H. Coulter Department of Biomedical Engineering

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I completed two degrees at Georgia Tech (biochemistry, earth & atmospheric sciences) with Highest Honors and an International Plan distinction for my completion of several semesters abroad. I also have multiple years of teaching experience as a teaching assistant for differential calculus, organic chemistry, and a first-year seminar course for earth & atmospheric sciences majors! I have also taught sustainability-related themes through different roles on and off campus. Currently, I am studying my Master's at the world's most sustainable university in the Netherlands, and hope to help you in whatever capacity I can from afar!

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User-moderated, email professors for graduate school.

How do you guys email professors for graduate school. I am looking to enroll in a masters program. Are professors more likely to respond if you apply for PhD. Also, my GPA is super low at 3.38. I have a double major in computational mathematics and CS. 3.455 Cs and 3.528 math. 3.82 combined for last 2 years of only math and CS classes. Was in a biomedical lab at UIUC in the past year as a software engineer, but the PI died. I got my BS from a university that ranked closed to 400 in the world for CS #engineering #software #swe #graduateschool

Do they remember you If not target the profs you did the best in

Well I am still working with the guy I did the most amount of work with. It is for a computer algebra system for classification of combinatorial objects - which I understand nothing of.

That's great you should have atleast 2 prof that know you

In the US, Master program is not funded by profs. So they won’t care and won’t reply. For PhD admissions, easiest way is to find out if they have funding, do some free work in their lab and get admission afterwards.

For Ms they'll typically say to do the generic application and if admitted then contact them. All they care about is Phd slaves 😜

Every once in a while and MS student email would interest me enough to respond. But there has to be something really good, like a personal connection, some highly relevant experience etc. But that might have been 2% of all the MS/intern etc spam I got. Source: ran 350 person MS program and was prof for 18 years.

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