Kit Rodolfa is the Research Director at the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford, working at the intersection of machine learning and public policy on using novel computational tools to modernize government and benefit society. His research interests include the bias, fairness, and interpretability of machine learning methods, as well as understanding and filling gaps between the theory and practice of machine learning.

Previously, Kit worked as a Senior Research Scientist for the Data Science and Public Policy Lab at Carnegie Mellon University and University of Chicago, where he contributed to public interest-focused machine learning projects, co-developed courses for both machine learning and public policy students, and helped run the Data Science for Social Good Summer Fellowship (DSSG). He also led the initial data science efforts at Devoted Health, and has served as Chief Data Scientist at Hillary for America, as the Director of Digital Analytics for the White House Office of Digital Strategy during the Obama administration, and on the analytics team during President Obama’s 2012 re-election campaign.

Kit holds a PhD in Stem Cell Biology and Master’s in Public Policy from Harvard University, MPhil in Chemistry from the University of Cambridge, and BS degrees in Physics and Chemistry from Harvey Mudd College.