Claire Boyd
she/her/hers
Claire is a graduate student at UChicago’s Masters in Computational Analysis and Public Policy Program (MSCAPP) at the Harris School of Public Policy. She is currently a data science intern at NYC Mayor’s Office of Technology and Innovation, working alongside city agencies to support data-driven policymaking. Before starting at Harris, Claire worked at the Urban Institute for four years, leaving as a research associate at the Racial Equity Analytics Lab (REAL) where she led projects that explore how philanthropic and public sector leaders can center equity in their programs and policies.
Ethan Arsht
he/him/his
Ethan Arsht is a graduate student in University of Chicago’s Masters in Computational Analysis and Public Policy Program. He currently interns at the Electoral Innovation Lab at Princeton University, where he applies computational methods to assess the extent and effects of gerrymandering. He previously worked as a data analyst for progressive political campaigns in the United States and Europe.
Jack Gibson
he/him/his
Jack Gibson is a master’s student at the University of Chicago studying computational analysis and public policy. He is currently a research assistant at the Metric Geometry and Gerrymandering Group, conducting research on alternative voting systems, redistricting, and election modeling. Before returning to school, he was a public policy analyst at National Journal.
Kayecee Palisoc
she/her/hers
Kayecee is a graduate student at the University of Chicago studying Computational Analysis and Public Policy. She is currently a Community Data Fellow at UChicago’s Data Science Institute, working with the State of Illinois Commission on Equity and Inclusion. Prior to coming to Chicago, she worked in the analytics space in various private industries in Manila Philippines and at the Asian Development Bank.
Madeleine Roberts
she/her/hers
Madeleine is a graduate student studying Computational Analysis and Public Policy at the University of Chicago. She is currently a Congressional Modernization Fellow for the U.S. House of Representatives’ Committee on House Administration, where she is assisting in the implementation of the House’s Artificial Intelligence Strategy, advising on cyber and technology issues, and creating technical products to increase the committee’s efficiency. Prior to graduate school, Madeleine conducted research in human-centered design, as well as worked as a North American Language and Cultural Assistant for the Spanish government.
Monica Nimmagadda
she/her/hers
Monica Nimmagadda is a dual master’s student (MPP/MBA) at the University of Chicago Harris School and Booth School. She is currently a Congressional Modernization Fellow for the House of Representatives Digital Service team, creating tools for Congress to work more efficiently and effectively. Prior to graduate school, she worked for the City of Baltimore’s Mayoral innovation team as Data Lead and in the Department of Housing and Community Development as Special Assistant to the Commissioner.