Joshua Blumenstock is an Assistant Professor at the U.C. Berkeley School of Information, and the Director of the Data-Intensive Development Lab. His research lies at the intersection of machine learning and development economics, and focuses on using novel data and methods to better understand the causes and consequences of global poverty. At Berkeley, Joshua teaches courses in machine learning and "data-intensive development". Previously, Joshua was on the faculty at the University of Washington, where he led the school’s Data for Social Good initiative. He has a Ph.D. in Information Science and a M.A. in Economics from U.C. Berkeley, and Bachelor’s degrees in Computer Science and Physics from Wesleyan University. He is a recipient of the Intel Faculty Early Career Honor, a Gates Millennium Grand Challenge award, a Google Faculty Research Award, and is a former fellow of the Thomas J. Watson Foundation and the Harvard Institutes of Medicine. His work has appeared in a variety of publications including Science, Nature, the American Economic Review, and the proceedings of KDD and AAAI.