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 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 policy events, including LGBT+ rights, cannabis legalization, and gun control legislation.
At the Immigration Policy Lab, my work involves developing machine learning methodology 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 refugees, with the goal of improving the ultimate economic outcome of these migrants.
I also hold an M.S. in Social Science from Caltech, an M.A. in International Policy from Stanford University, and a B.A. in Political Science from the University of California, Santa Barbara.
My forthcoming book, “Securing Elections: How Data-Driven Election Monitoring Can Improve Democracy,” co-written with R. Michael Alvarez, Seo-young Silvia Kim, and Yimeng Li, is due to publish under Cambridge University Press in 2020.