Teaching

Political Science Laboratory (Undergraduate, Co-Instructor with Hao Zhang, Spring 2024)

The Political Science Laboratory introduces undergraduate political scientists to the basic quantitative tools of political science research. The class explores the key statistical and computational research tools that social scientists use to frame and answer empirical questions. One focus of the class is causal inference: How can we tell causation from mere association?

Math Camp I (Graduate, Co-Instructor with Hao Zhang, August 2022, August 2023)

The Math Prefesher is designed to introduce and review core mathematics and programming prerequisites that students need to be successful in the graduate quantitative methods courses in the Political Science department and elsewhere at MIT.

Quantitative Research Methods II: Causal Inference (Graduate, Teaching Assistant, Spring 2021)

Research design and statistical methods for causal inference, including experiments, matching, regression, panel methods, difference-in-differences, synthetic control methods, instrumental variable estimation, regression discontinuity designs, causal mediation analysis, nonparametric bounds, and sensitivity analysis.
Student Rating: 6.9 out of 7

Global Diversity Lab Summer Internship Program (Mentor, Summer 2023)

Additional Training: Kaufman Teaching Certificate Program (Fall 2023)