Kevin Leyton-Brown is professor of computer science at the University of British Columbia. He holds a PhD and M.Sc. from Stanford University (2003; 2001) and a B.Sc. from McMaster University (1998). Much of his work is at the intersection of computer science and microeconomics, addressing computational problems in economic contexts and incentive issues in multiagent systems. He also studies the application of machine learning to the automated design and analysis of algorithms for solving hard computational problems. He is a core member of our team working on the FCC incentive auction driving innovative software research.
Kevin has co-written two books, “Multiagent Systems” and “Essentials of Game Theory,” and over eighty peer-refereed technical articles, and co-taught the Coursera course “Game Theory” to over 130,000 students. With his coauthors, he has received paper awards from JAIR, ACM-EC, AAMAS and LION, and numerous medals for the portfolio-based SAT solver SATzilla at international SAT competitions (2003-12). He was program chair for the ACM Conference on Electronic Commerce (ACM-EC) in 2012, and serves as an associate editor for the Journal of Artificial Intelligence Research (JAIR), the Artificial Intelligence Journal (AIJ), and ACM Transactions on Economics and Computation. He split his 2010-11 sabbatical between Makerere University in Kampala, Uganda, and the Institute for Advanced Studies at Hebrew University in Jerusalem, Israel. He has served as a consultant for Trading Dynamics Inc., Ariba Inc., and Cariocas Inc., and was scientific advisor to Zite Inc until it was acquired by CNN in 2011.