teaching
Courses as TA/special reader and mentorship experience.
University of Washington 2025–present
- Mentor, Statistical Modeling Team, Summer Institute in Computational Social Science (SICSS-UW), University of Washington, 2026. Bayesian measurement-error modeling and calibration for web-scale AI content detection
UCLA 2021–2025
Teaching Assistant, Department of Biostatistics, UCLA
- Biostatistics 250C: Multivariate Biostatistics, Instructor: Prof. Donatello Telesca
Theory and methods for multivariate linear models, graphical models, component analysis, factor analysis, clustering, discriminant analysis, models for longitudinal and clustered data. - Biostatistics 250B: Linear Statistical Models, Instructor: Prof. Weng Kee Wong
Theory of linear models, linear mixed models, model misspecification, ridge regression, Bayesian estimation in linear models, REML, prediction, and model selection. - Biostatistics 241: Spatial Modeling and Data Analysis, Instructor: Prof. Sudipto Banerjee
Statistical theory and foundations for carrying out inference on spatially referenced datasets, computational methods and algorithms. Practical examples and applications demonstrated using BUGS, JAGS and NIMBLE software packages in R.
Special Reader, Department of Biostatistics, UCLA
- Biostatistics 255A: Advanced Probability and Statistics, Instructor: Prof. Sudipto Banerjee
Topics in measure theoretic probability including set theory, analysis, probability measure, Caratheodory extension theorem, Borel-Cantelli lemmas. - Biostatistics 255B: Advanced Probability and Statistics, Instructor: Prof. Sudipto Banerjee
Topics in measure theoretic probability including random variables, product measure, expectation, inequalities, convergence, law of large numbers, Radon-Nykodym theorem.
India 2019–2021
- Instructor for Mathematics Competitions, RKMV Narendrapur