Teaching

Teaching at George Mason University

• STAT 344: Probability and Statistics for Engineers and Scientists I
  Undergraduate course covering basic probability, discrete and continuous random variables, the Central Limit Theorem, and statistical inference for means and proportions
  [Fall ’25 Syllabus]

Teaching at the University of South Carolina

• STAT 515: Statistical Methods I
  Undergraduate course covering basic probability, statistical inference for means and proportions, analysis of variance (ANOVA), and simple linear regression
  [Spring ’25 Syllabus] [Spring ’25 Class Schedule]


• STAT 517: Advanced Statistical Models
  Undergraduate course covering generalized linear models (GLMs), random effects and mixed effects models, and nonparametric and semiparametric models
  [Fall ’24 Syllabus] [Fall ’24 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, Markov chain Monte Carlo (MCMC), Dirichlet processes, and reinforcement learning
  [Spring ’24 Syllabus] [Spring ’24 Class Schedule]