He is a Professor of Public Policy at Harvard Kennedy School and an affiliate faculty member in Computer Science.
He look at public policy through the lens of computer science, bringing a computational perspective to a diverse range of contemporary social issues. My recent work has examined policing practices, including the development of statistical tests for discrimination; fair machine learning, including in automated speech recognition; and democratic governance, including swing voting, polling errors, voter fraud, and political polarization.
Before joining Harvard, he was on the faculty at Stanford University, with appointments in management science & engineering, computer science, sociology, and law school. At Stanford, he was the founding director of the Computational Policy Lab. The lab is comprised of researchers, data scientists, and journalists who work to address policy problems through technical innovation. For example, we deployed a “blind charging” platform across California to mitigate racial bias in prosecutorial decisions. We also collected, released, and analyzed data on over 100 million traffic stops as part of our Open Policing Project.
