Sharad Goel is an assistant professor at Stanford in the Department of Management Science & Engineering (in the School of Engineering), with courtesy appointments in Sociology and Computer Science.
His primary area of research is computational social science, an emerging discipline at the intersection of computer science, statistics, and the social sciences. He has a particular interest in applying modern computational and statistical techniques to understand and improve public policy; his work has focused recently on stop-and-frisk, tests for racial bias, algorithmic fairness, swing voting, voter fraud, filter bubbles, and online privacy. He also helped start the Stanford Open Policing Project, a repository of data on over 100 million traffic stops across the United States.
Sharad 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, he worked at Microsoft Research in New York City.