Jae Yeon Kim

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Advisors: 
Taeku Lee and Paul Pierson (co-chairs)
Subfields: 
Computational Social Science
Political Behavior
Racial and Ethnic Politics
Personal Statement: 

I am a behavioral data scientist and a PhD candidate in Political Science at UC Berkeley.  I am also a data science fellow for the Data-intensive Social Sciences Lab (D-Lab), a data science education program fellow at UC Berkeley, and a co-organizer for the upcoming Summer Institute in Computational Social Science in the San Francisco Bay Area.

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 (evaluation). 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've taught computational social science at the graduate level as a lead instructor. I am passionate about making data science accessible.

To visit my website, click here.

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