I am an Assistant Professor in the Department of Political Science at The University of Chicago. I also have affiliations with the Department of Statistics, the Committee on Data Science, and the PhD program in political economy.

My work on statistical methodology for social science research integrates machine learning methods with experimental design to answer causal questions. I also have an ongoing substantive research program that examines online behavior to understand how people change their views and attitudes in response to the conversations they take part in and the information they engage with online. I combine these agendas in social media experiments, using approaches like adaptive assignment and policy learning, and incorporating natural language processing methods for flexible conversational interventions. I was awarded an Andrew Carnegie Fellowship in 2024 to advance this research agenda.

My research has been supported by the National Science Foundation Methodology, Measurement, and Statistics (MMS) program, the Carnegie Corporation of New York, the Vaccine Confidence Fund, and The University of Chicago’s Data & Democracy Research Initiative.

Previously, I was a post-doctoral fellow in Susan Athey’s Golub Capital Social Impact Lab at the Stanford Graduate School of Business. My PhD is from Yale, joint in Political Science and Statistics & Data Science; I have a Masters degree in Public Affairs from the Princeton School of Public and International Affairs; and my undergraduate degree is from Grinnell College.

After college, I spent a fellowship year in Lesotho, and two years in Madagascar as a Peace Corps volunteer. Prior to my PhD, I worked on policy research for several years in West Africa with the World Bank and the United Nations.