Teaching

University of South Carolina

Graduate Courses

• STAT 714: Linear Statistical Models (Fall 2020, Fall 2021, Fall 2022)
  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 (Spring 2021)
  Graduate course covering supervised and unsupervised machine learning, optimization algorithms for big data, sparse statistical modeling, and structured sparsity regularization
  [Spring ’21 Syllabus] [Spring ’21 Class Schedule] [Some nice plots made by students in STAT 718]


• STAT 721: Stochastic Processes (Spring 2022)
  Graduate course covering point processes, mathematical finance, Gaussian processes, reinforcement learning, Markov chain Monte Carlo (MCMC), and Dirichlet processes
  [Spring ’22 Syllabus] [Spring ’22 Class Schedule] [Some nice plots made by students in STAT 721]

Undergraduate Courses

• STAT 517: Advanced Statistical Models (Fall 2022)
  Undergraduate course covering generalized linear models (GLMs), random effects and mixed effects models, nonparametric and semiparametric models, and penalized regression models
  [Fall ’22 Syllabus] [Fall ’22 Class Schedule]

University of Florida

• STA 3024: Introduction to Statistics II (Spring 2016)
  Undergraduate course covering hypothesis tests and confidence intervals (both parametric and nonparametric), one-way and two-way analysis of variance (ANOVA), simple and multiple linear regression, and categorical data analysis
  [Spring ’16 Syllabus] [Spring ’16 Class Schedule]