All my class webpages are on Blackboard. Below are the most recent syllabi and class schedules from the classes I teach.

  • STAT 517: Advanced Statistical Models
    Undergraduate course covering generalized linear models (GLMs), random effects and mixed effects models, and nonparametric and semiparametric models
    [Fall ’22 Syllabus] [Fall ’22 Class Schedule]

  • STAT 714: Linear Statistical Models
    Graduate course covering matrix algebra, estimation and inference for linear models, Gauss Markov and generalized least squares models, and shrinkage methods
    [Fall ’22 Syllabus] [Fall ’22 Class Schedule]

  • STAT 718: High-Dimensional Data
    Graduate course covering supervised learning, unsupervised learning, methodology for big data, numerical optimization, and deep learning and deep generative models
    [Spring ’23 Syllabus] [Spring ’23 Class Schedule]

  • STAT 721: Stochastic Processes
    Graduate course covering point processes, mathematical finance, Gaussian processes, reinforcement learning, Markov chain Monte Carlo (MCMC), and Dirichlet processes
    [Spring ’24 Syllabus] [Spring ’24 Class Schedule]