I am a computational social scientist and a PhD candidate in Political Science at UC Berkeley. I am also a D-Lab Data Science Fellow, a Data Science Education Program Fellow at UC Berkeley, and an incoming Insight Data Science Fellow.
I use behavioral science, statistics, and data science tools to study how people think and behave with a focus on diversity and inclusion issues. Specifically, my research has focused on two questions: first, how minority group members experience racial bias (measurement) and second, how that affects the ways in which these people form political identities, attitudes, and behavior (causal inference). My award-winning dissertation applies computational, statistical, and qualitative methods to understand what unites racial minority groups in the United States. My most recent research interest is narrowing the gap between the ethics and practice of using machine learning.
I am a proud recipient of the Outstanding Graduate Student Instructor Award. I’ve taught computational social science at the graduate level as a lead instructor. I am passionate about making data science accessible.