Graduate Programs in Mathematics

The Mathematics Department is involved with three programs of graduate study. In addition to the Mathematics graduate program (MATH), the Department offers a program in Mathematical Statistics (STAT) and significantly participates in an interdisciplinary program in Applied Mathematics & Statistics, and Scientific Computation (AMSC).

Graduate Study in Mathematics

The Mathematics Department offers a rich and varied program of graduate study in mathematics. Through coursework and the writing of a thesis, students are prepared for careers in teaching and research in the mathematical sciences and their applications. Graduate students in any one of these programs can take courses across all three, and it is relatively simple to transfer between programs.

Research and Teaching Opportunities

Graduate students play a vital role in the research and teaching activities of the department. The full-time graduate student enrollment in all three degree programs is approximately 200, with many part-time students from the local professional community also enrolled.

Course Offerings

Course offerings are organized into general fields such as: Algebra and Number Theory, Complex Analysis, Logic, Numerical Analysis, Ordinary Differential Equations and Dynamical Systems, Partial Differential Equations, Real and Functional Analysis, Statistics, Probability, and Topology and Geometry.

First-year graduate courses are taught every year in each field, with an average enrollment of 15-25 students. In these courses, students acquire the basic techniques necessary for research in mathematics and applied areas. Additionally, many advanced courses are offered in specialized topics that introduce students to areas of active research. The department offers around twenty advanced graduate courses each semester, making it possible to explore a wide range of topics. A list of faculty research interests can be seen here.

Advanced Undergraduate Courses

The department also offers a wide range of advanced undergraduate courses, providing an introduction to many areas of mathematics including geometry, probability, topology, numerical analysis, logic, and differential equations.

Ph.D. Degree Requirements

The requirements for the Ph.D. are similar across the three programs. Students must first take a set of written qualifying exams on material from basic first-year graduate courses. After passing these exams, they take advanced courses in a particular area to begin preparing for thesis work. A total of 36 credits (12 one-semester courses) is required for the Pure Mathematics Ph.D., while a total of 30 credits is required for the Ph.D. in Statistics. Admission to candidacy for the Ph.D. is granted after passing an oral examination based on advanced coursework or research papers. The dissertation is then written under the guidance of a faculty member, with the final thesis defense being an oral examination by a committee of faculty members.

M.A. Degree Requirements

The M.A. degree is granted to students who complete 24 credits of coursework and write a master's thesis. Alternatively, students may opt for a non-thesis M.A., which requires 30 credits of coursework and successful completion of the written qualifying exams at the master's level.

Policies and Expectations

Expectations for doctoral students and faculty are detailed in the Policies of the Graduate Program in Mathematics.

Archives: F2011-S2012 F2012-S2013 F2013-S2014 F2014-S2015 F2015-S2016 F2016-S2017 F2017-S2018 F2018-S2019 F2019-S2020 F2021-S2022 F2022-S2023 F2023-S2024 

  • Numerical Analysis for Operator Learning in SciML

    Speaker: Christoph Schwab (ETH Zurich) - https://math.ethz.ch/research/applied-mathematics-numerical-analysis-scientific-computing/christoph-schwab.html

    When: Tue, September 3, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Aziz Lecture: Multilevel approximation of Gaussian random fields

    Speaker: Christoph Schwab (ETH Zurich) - https://math.ethz.ch/research/applied-mathematics-numerical-analysis-scientific-computing/christoph-schwab.html

    When: Wed, September 4, 2024 - 3:15pm
    Where: Kirwan Hall 3206
  • Runge-Kutta methods are stable

    Speaker: Eitan Tadmor (University of Maryland) - https://www.math.umd.edu/~tadmor/

    When: Tue, September 10, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Weights and applications in numerics

    Speaker: Abner Salgado (University of Tennessee, Knoxville) - https://sites.google.com/utk.edu/abnersg/

    When: Tue, September 17, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=0f98cef1-69eb-46de-8c5b-b1ee0158fd27
  • Multilevel diffusion: Infinite dimensional score-based diffusion models

    Speaker: Nicole Tianjiao Yang (Emory University) - https://nicoletyang.github.io/

    When: Tue, September 24, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=434417b2-66a7-4fa5-bef1-b1f5015ed100
  • Numerical schemes for solving the Cahn-Hilliard equation and other energy based systems

    Speaker: Giordano Tierra (University of North Texas) - https://www.math.unt.edu/~gt0141/

    When: Tue, October 1, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Nonlocal Attention Operator: Towards an Interpretable Foundation Model for Physical Systems

    Speaker: Yue Yu (Lehigh University) - https://www.lehigh.edu/~yuy214/

    When: Tue, October 8, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6eb7ec88-a299-4d1d-b3da-b203015f7839
  • Stochastic-Gradient-based Algorithms for Solving Nonconvex Constrained Optimization Problems

    Speaker: Frank E. Curtis (Industrial and Systems Engineering, Lehigh University) - https://coral.ise.lehigh.edu/frankecurtis/

    When: Tue, October 15, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=926453eb-5a94-4eab-a948-b20a01565457
  • Multiphysics problems related to brain clearance, sleep and dementia

    Speaker: Kent Mardal (University of Oslo ) - https://kent-and.github.io/

    When: Tue, October 22, 2024 - 3:30pm
    Where: Online
  • AdaBB: A Parameter-Free Gradient Method for Convex Optimization

    Speaker: Shiqian Ma (Rice University) - https://sqma.rice.edu/

    When: Tue, October 29, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=c0d1241c-6522-4b1a-8bc3-b21801583843
  • Macroscopic Dynamics for Chemical Reactions: Large deviation and Wasserstein diffusion approximation

    Speaker: Yuan Gao (Purdue University) - https://yuangaogao.github.io/

    When: Tue, November 5, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=5a47c268-2e27-4756-83e5-b21f016ce455
  • Learning a robust shape parameter for radial basis functions approximation with continual learning

    Speaker: Maria Han Vega (Ohio State University) - https://hanveiga.com/

    When: Tue, November 12, 2024 - 7:45am
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=686113c1-afc6-41d1-9234-b226016b1838
  • Canceled

    When: Tue, November 19, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Transport information geometric computations

    Speaker: Wuchen Li (University of South Carolina) - https://people.math.sc.edu/wuchen/

    When: Tue, December 3, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=73c2db92-b497-442d-8408-b23b01759321
  • Quantum Eigenvalue(phase) Estimation: From Quantum Data to Classical Signal Processing

    Speaker: Zhiyan Ding (University of California, Berkeley) - https://math.berkeley.edu/~zding.m/

    When: Thu, December 12, 2024 - 2:00pm
    Where: Kirwan Hall 3206
  • Some progress on low rank methods for time dependent equations

    Speaker: Yingda Cheng (Virginia Tech) - https://yingdacheng.github.io/

    When: Tue, February 4, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=403cf24f-05f9-466b-85aa-b27a01681c5d
  • Optimal Sampling in Least-Squares Methods

    Speaker: Albert Cohen (Sorbonne Université) - https://www.ljll.fr/cohen/

    When: Tue, February 11, 2025 - 3:30pm
    Where: https://umd.zoom.us/j/97661035379?pwd=eW4xR2xFL3paQ3VCTXd6bjNXNlJNUT09
  • Dynamic Generative AI for Uncertainty Quantification

    Speaker: Feng Bao (Florida State University) - https://www.math.fsu.edu/~bao/

    When: Tue, February 25, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=dcea5240-c0b4-4f77-8136-b28f01651d49
  • Computation of origami-inspired structures and mechanical metamaterials

    Speaker: Frederic Marazzato (University of Arizona) - https://sites.google.com/view/marazzaf/home

    When: Tue, March 11, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8796cc66-27e8-42b9-8b36-b29d015a0c76
  • TBA

    Speaker: TBA (TBA) - TBA

    When: Tue, March 25, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Discontinuous Galerkin methods for Maxwell’s equations

    Speaker: Peter Monk (University of Delaware) - https://sites.udel.edu/monk/

    When: Tue, April 1, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=33f49515-d74a-4435-95bb-b2b2015a30d4
  • On the Local Linear Convergence of ADMM for Solving SDPs under Strict Complementarity

    Speaker: Heng Yang (Harvard University) - https://hankyang.seas.harvard.edu/

    When: Tue, April 8, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bf9b52ab-5228-4a5c-a284-b2b9016002e1
  • Data Driven Modeling for Scientific Discovery and Digital Twins

    Speaker: Dongbin Xiu (The Ohio State University) - https://sites.google.com/view/dongbin-xiu

    When: Tue, April 15, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=1ae71f02-8959-4058-ba58-b2c001597272
  • 𝐻² conforming virtual element discretization of nondivergence form elliptic equations

    Speaker: Guillaume Bonnet (Université Paris-Dauphine) - https://www.ceremade.dauphine.fr/~bonnet/

    When: Thu, April 17, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=de71a275-f7f9-4400-998b-b2c70168c62a
  • Quantum signal processing and nonlinear Fourier analysis: a dialogue

    Speaker: Lin Lin (University of California, Berkeley) - https://math.berkeley.edu/~linlin/

    When: Tue, April 22, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8c974a95-1ae5-45df-95bc-b2c7016768ee
  • Martingale deep learning for very high-dimensional quasi-linear partial differential equations and stochastic optimal controls

    Speaker: Wei Cai (Southern Methodist University) - https://people.smu.edu/cai/

    When: Tue, April 29, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Applied Math Colloquium: The Mean-Field Ensemble Kalman Filter

    Speaker: Andrew Stuart (California Institute of Technology) - https://www.eas.caltech.edu/people/astuart

    When: Tue, May 6, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Aziz Lecture: Allowing Image And Text Data To Communicate

    Speaker: Andrew Stuart (California Institute of Technology) - https://www.eas.caltech.edu/people/astuart

    When: Wed, May 7, 2025 - 3:15pm
    Where: Kirwan Hall 3206