Teaching

In the 2024-25 academic year, I am a teaching assistant for 14.30: Introduction to Probability for Economists (Fall) and 14.382: Algorithms and Behavioral Science (Spring).

In past, I have been a teaching assistant for several methods courses:

  1. 14.385: Nonlinear Econometrics
    MIT, graduate, Fall 2021
    This course is part of MIT’s core PhD econometrics sequence, typically taken at the start of the second year. Topics include bootstrap, method of simulated moments, partial identification, and debiased machine learning.
    [Student Reviews]

  2. 14.32: Econometric Data Science
    MIT, undergraduate, Fall 2021
    This is the second course in MIT’s undergraduate econometrics sequence. It covers inference, potential outcomes and causal inference, regression, instrumental variables, regression discontinuity, panel data, and time series.
    [Student Reviews]

  3. Stat 111: Introduction to Theoretical Statistics
    Harvard, undergraduate, Spring 2016
    This is the second course in Harvard’s undergraduate statistics concentration. It covers hypothesis testing and confidence intervals, method of moments, maximum likelihood, Bayesian inference, and linear regression.
    [Student Reviews] [Materials]