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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]