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 founded and direct 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. If you’re a Stanford undergrad interested in working with us, please apply through the department’s 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!