Regular biography
Kevin Leyton-Brown is a Professor of Computer Science and an Associate Member of the Vancouver School of Economics at The University of British Columbia. His research focuses on artificial intelligence, particularly at the intersection of machine learning and market design and analysis, computational game theory, behavioral models, and the design of heuristic algorithms. He obtained his Ph.D. from Stanford University in 2003. His teaching and research are aligned with the department's focus on computational economics and related methodologies.
Scholar-generated biography
Kevin Leyton-Brown is a Professor of Computer Science at the University of British Columbia and holds the Canada CIFAR AI Chair. His research focuses on artificial intelligence, machine learning, game theory, algorithms, and market design. His work explores algorithmic foundations of multiagent systems, optimization techniques for algorithm configuration, and the application of game theory to market mechanisms. He has contributed to the development of frameworks for automated algorithm selection and hyperparameter optimization, as well as studies on combinatorial auctions and Bayesian optimization. His research bridges theoretical and applied aspects of AI, with a strong emphasis on empirical evaluation and practical implementation.