Graduate Special Topics

Department: 
MATH
Course Number: 
8803
Hours - Lecture: 
3
Hours - Total Credit: 
3
Typical Scheduling: 
Every Fall and Spring Semester

The following table contains a list of all graduate special topics courses offered by the School of Math within the last 5 years. More information on courses offered in the current/upcoming semester follows below. 

 

Semester Instructor         Title                                                  
Spring 2026 Hannah Choi Neuronal Dynamics and Networks
  Christian Houdré From Longest Increasing Subsequences in Random Words to Quantum Statistics, II
  Thang Le Introduction to Quantum Topology
  Anton Zeitlin Representation Theory II
Fall 2025 Matt Baker Matroid Theory
  John Etnyre Manifolds and Handlebodies
  Xiaoyu He Ramsey and Turan Theory
  Christian Houdré From Longest Increasing Subsequences in Random Words to Quantum Statistics
  Tobias Ried Optimal Transport: Theory and Applications
  Anton Zeitlin Representation Theory
  Wei Zhu Mathematical Foundations of Machine Learning
Spring 2025 Gong Chen Nonlinear Dispersive Equations
  Alex Dunn Analytic Number Theory II
  Jen Hom Knot Concordance and Homology Cobordism
  Heinrich Matzinger AI, Transformers, and Machine Learning Methods: Theory and Applications
Fall 2024 Alex Blumenthal Big and Noisy: Ergodic Theory for Stochastic and Infinite-Dimensional Dynamical Systems
  Mohammad Ghomi Geometric Inequalities
  Michael Lacey Discrete Harmonic Analysis
  Rose McCarty Structure for Dense Graphs
  John McCuan Mathematical Capillarity
  Haomin Zhou Machine Learning Methods for Numerical PDEs
Spring 2024 Anton Bernshteyn Set Theory
  Greg Blekherman Convex Geometry
  Hannah Choi Mathematical Neuroscience
  Alex Dunn Analytic Number Theory I
  John Etnyre 3-Dimensional Contact Topology
  Chongchun Zeng Topics in PDE Dynamics II
Fall 2023 Jen Hom Knots, 3-Manifolds, and 4-Manifolds
  Tom Kelly Absorption Methods for Hypergraph Embeddings and Decompositions
  Zhiwu Lin Topics in PDE Dynamics I
  Galyna Livshyts Concentration of Measure and Convexity
  Cheng Mao Statistical Inference in Networks
Spring 2023        Igor Belagradek Diffeomorphism Groups
Fall 2022 Hannah Choi Neuronal Dynamics and Networks
  John Etnyre Topics in Algebraic Topology
  Christopher Heil     Measure Theory for Engineers
Fall 2021 Anton Bernshetyn Descriptive Combinatorics
  John Etnyre The Topology of 3-Manifolds
  Christopher Heil Measure Theory for Engineers
  Zhiyu Wang Spectral Graph Theory

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In the lists below, Math 8803-XXX refers to the special topics course taught by the instructor whose last name begins with XXX. 

 

 

Prerequisites: 

Spring 2026: 

Math 8803-CHO: MATH 2552 (Differential Equations) or equivalent*. Familiarity with Python, MATLAB, or other programming languages

Math 8803-HOU: Math 6241 and 6242, and Part I of the course. Some familiarity with Brownian motion, random matrices, and non-parametric statistics will also be assumed. 

Math 8803-TLE: Math 6121 and 6441

Math 8803-ZEI: Math 6121 and 6452 recommended, or agreement of the instructor, and part I of the course. This course assumes familiarity with representations of Lie algebras and groups, as covered in a first course on representation theory.

 

*Note that undergraduate-level prerequisites for graduate courses are not checked by the registration system.

Course Text: 

Spring 2026: 

Math 8803-CHO: See syllabus

Math 8803-HOU: See syllabus

Math 8803-TLE: See syllabus

Math 8803-ZEI: See syllabus

 

 

 

Topic Outline: 

Spring 2026: 

Math 8803-CHO: This course covers various topics in neural dynamics at the level of single cell and population, and  their connections to biological neural networks. 

 

Math 8803-TLE: Topics include the Jones polynomial and quantum link invariants,  Topological Quantum Field Theory (ribbon and modular tensor categories), quantum representations of mapping class groups, and skein modules/algebras. 

 

Math 8803-HOU: The course will cover the following sequence of topics: 

Introduction

Weak Invariance Principles

Longest Increasing Subsequences:  The One Sequence Case

Maximal Eigenvalues of Matrices from the Gaussian Unitary Ensemble

Young Diagrams and the RSK Algorithm 

Convergence of the Shape of RSK Young Diagrams

Spectra of GUE and Related Gaussian Matrices

A Conjecture for Markov Random Words

Two or More Random Words, Longest Common (and Increasing) Subsequences 

Strong Invariance Principles and Rates of Convergence

Quantum Tomography

Quantum Estimation

 

 

Math 8803-ZEI: In the first part, we will continue studying representations of classical complex Lie algebras, followed by representations of compact Lie groups and the Peter-Weyl theorem. We will explore applications, including an explicit study of the hydrogen atom from a representation-theoretic perspective. The course then covers the structure of Lie groups, including the classification of compact and complex reductive groups, the topology of Lie groups and homogeneous spaces, and the Bruhat decomposition.

The second part is devoted to advanced topics in modern representation theory: representations of affine Lie algebras, elements of vertex algebra theory, and quantum groups. Topics include highest-weight representations of affine Lie algebras, constructions of vertex algebras with applications to conformal field theory, and quantum groups in the context of knot invariants and quantum topology.