Hi There!

I’m a PHD candidate in political science and statistics at MIT. My research focuses on the intersection of machine learning and causal inference with applications to electoral politics and public opinion.

My dissertation project develops a toolkit for conducting causal inference with bundled treatments. Conventional approaches to causal inference assume the researcher observes a single binary treatment, but some of the most important variables in political science, like race, democracy, or national power, exist as complex combinations of other traits. I propose a novel estimand developed specifically for such bundled treatments and provide a bounding approach to estimation to accompany it.

My substantive research focuses on public opinion and electoral politics, where I’ve also studied the effects of minimum wage increases on voter turnout, electoral volatility, and the effect of conjoint analysis on social desirability bias.