I am a Ph.D. candidate in the Political Economy program at the Stanford Graduate School of Business.

My research focuses on the interplay between information and political preference based on game theory and behavioral political economy. On the empirical front, I use machine (reinforcement) learning methods for implementing adaptive experiments and various causal inference methods to analyze survey experiments and observational data on the US Congress.

During graduate study, I worked on data science problems at Netflix. I received my masters in Statistics from the Department of Statistics at Stanford in 2023, where I focused on causal inference methods for observational panel data, experimental design, and stochastic processes.

Prior to joining GSB, I worked at Analysis Group. I graduated from Middlebury College in 2016 with a B.A in economics and a minor in political science.