I am an Applied Research Statistician at Harvard Law School, where I work on my own research in addition to providing empirical and computational research support across Law School faculty- and student-led projects. I am also a researcher with Everyday Respect, a collaboration of social scientists and computer scientists aimed at building community-informed artificial intelligence (AI) tools for studying communication between officers and drivers during traffic stops. I received my Ph.D. in Political Science and International Relations from the University of Southern California (USC), where I was a Graduate Research Associate in both the Democracy and Fair Elections Lab and the Security and Political Economy Lab. I also hold a Master of Public Policy from USC's Sol Price School of Public Policy, where I specialized in applied econometrics for program evaluation.

Substantively, I study political representation, racial identity, and legislatures; electoral reform and election law; and the policy, design, and implementation of AI tools in government, particularly in policing. Methodologically, I apply causal inference and computational social science tools to the study of political institutions. My work has been published in the Journal of Race, Ethnicity, and Politics, the Journal of Experimental Political Science, Political Research Quarterly, and the Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL).

To support my own research and the research of others, I developed and maintain TextViz Studio, a no-code web application for social scientists that makes advanced text analysis and statistical modeling more accessible and intuitive. Outside of academia, I enjoy doing ceramics, studying languages, reading, and photography.