I received my PhD in Political Methodology and American Politics from Harvard University in April 2019. My research interests leverage cutting-edge methods in computer science and causal inference to answer substantive questions about public opinion, voting patterns, and elite behavior. Additionally, I produce open-source tools to help survey researchers conduct more efficient and unbiased research. I am committed to research transparency and open science.
In my dissertation, I build, test, and experimentally validate a computational model to estimate partisanship from free text. I extend this model to predict the relative biases of public opinion survey questions and show that voters respond predictably to texts with varying bias. Furthermore, I show that survey firms have consistently trended toward writing more conservative questions over the past two decades.