Hello! I am currently a Postdoctoral Fellow at Stanford's Immigration Policy Lab and a research associate with the Caltech/MIT Voter Technology Project's Monitoring the Election group. I received my Ph.D. in Social Science from the California Institute of Technology in 2019, focusing on developing and adapting novel quantitative methods in political science.
My research focuses on voter behavior and public opinion formation through the interactions between politicians, their constituents, and media institutions. I utilize original social media datasets, natural language processing, and econometric techniques aimed to better understand public reaction to major events, including LGBT+ rights, gun control legislation, and the #metoo movement.
At the Immigration Policy Lab, my work involves developing, adapting, and refining machine learning methodologies to match incoming refugees to landing locations in a host country. Leveraging large governmental datasets, the GeoMatch team and I apply learned models that recommend optimal landing locations to incoming migrants, with the goal of improving the ultimate economic outcomes.
I also hold an M.S. in Social Science from Caltech, a Master's in International Policy from Stanford University, and a B.A. in Political Science from the University of California, Santa Barbara.
My book, “Securing Elections: How Data-Driven Election Monitoring Can Improve Democracy,” co-written with R. Michael Alvarez, Seo-young Silvia Kim, and Yimeng Li, was published under Cambridge University Press in 2020.