Teaching at the University of Michigan
-
BIOSTAT 602: Biostatistical Inference
Graduate-level statistical course covering theoretical foundations of statistical reasoning and inference.
-
BIOSTAT 664: Special topics on applied mathematical models
Graduate-level seminar-style course on computation and bio-medical applications of mathematical models, such as differential equations and stochastic processes.
Teaching at UCLA and Duke
- Introduction to OHDSI tutorial
- STA 101: Data Analysis and Statistical Inference
-
STA 199: Intro to Data Science
Hands-on instruction supporting early data science training and practical computing skills.
-
STA 723: Statistics Case Studies
Included a workshop on high-performance cluster usage for computational workflows.
-
STA 601: Bayesian Methods and Modern Statistics
Supported Bayesian modeling instruction and computational lab sessions.
-
Duke Statistical Science Bootcamp
Bootcamp materials for foundational computing and statistics preparation.