Hello! I’m an assistant professor at Stanford University in the Department of Management Science & Engineering, in the School of Engineering. I also have courtesy appointments in Computer Science, Sociology, and the Law School.
I look at public policy through the lens of computer science, bringing a computational perspective to a diverse range of contemporary social issues. Some topics I’ve recently worked on are: policing practices, including statistical tests for discrimination; fair machine learning, including in automated speech recognition; and U.S. elections, including swing voting, polling errors, voter fraud, and political polarization.
I'm the founder and faculty director of the Stanford Computational Policy Lab. We’re a team of researchers, data scientists, and journalists that addresses policy problems through technical innovation. For example, we recently deployed a “blind charging” platform in San Francisco to mitigate racial bias in prosecutorial decisions. We also collected, released, and analyzed data on over 100 million traffic stops as part of the Stanford Open Policing Project. If you’re a Stanford undergrad interested in working with us, please apply through our department-wide Diversity in Research program.
Sometimes I write essays about policy issues from a statistical perspective. These include discussions of algorithms in the courts (in the New York Times, the Washington Post, and the Boston Globe); policing (in Slate and the Huffington Post); mass incarceration (in the Washington Post); election polls (in the New York Times); claims of voter fraud (in Slate, and also an extended interview with This American Life); and affirmative action (in Boston Review).
I studied at the University of Chicago (B.S. in Mathematics) and at Cornell (M.S. in Computer Science; Ph.D. in Applied Mathematics). Before joining the Stanford faculty, I worked at Microsoft Research in New York City.
If you would like to chat, please send me an email!