Kevin Leyton-Brown studies artificial intelligence, exploring the critical interplay of machine learning with either the architecture of electronic markets or the development of heuristic algorithms.

Kevin Leyton-Brown is a  Professor of Computer Science and a Distinguished University Scholar at the University of British Columbia, holding a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute. He is also an associate member of the Vancouver School of Economics. He earned his PhD and M.Sc. from Stanford University (2003, 2001) and a B.Sc. from McMaster University (1998).

His impactful work spans the intersection of artificial intelligence and economics. He notably contributed to the design of a government auction that reallocated North American radio spectrum and an electronic market connecting Ugandan farmers with buyers for surplus crops. Leyton-Brown has also developed widely used open-source software, including  SATzilla (an algorithm portfolio for satisfiability problems), Mechanical TA (peer grading software used globally), and AutoWEKA (a machine learning tool for model selection and hyperparameter optimization). He is increasingly focused on large language models, particularly their role as components in agent architectures, driven by a belief in leveraging AI for the benefit of underserved communities, especially in the developing world.

A prolific researcher, Leyton-Brown has co-authored over 175 peer-refereed technical articles, accumulating over 28,000 citations and an h-index of 62. His significant contributions have earned him fellowships with the Royal Society of Canada (2023), the Association for Computing Machinery (2020), and the Association for the Advancement of Artificial Intelligence (2018). He was part of the team that won the prestigious 2018 INFORMS Franz Edelman Award, recognized as the leading award in operations research and analytics. His accolades include UBC's 2015 Charles A. McDowell Award for Research Excellence, a 2014 NSERC E.W.R. Steacie Memorial Fellowship, and the 2013 Outstanding Young Computer Science Researcher Prize from the Canadian Association of Computer Science. Additionally, he and his coauthors have received numerous paper awards from top-tier venues like AIJ, JAIR, ACM-EC, and KDD, along with multiple medals in international SAT solver competitions.

Beyond research, Leyton-Brown is dedicated to education. He has co-authored two popular textbooks and co-taught two highly successful Coursera courses on "Game Theory," reaching over a million students (and counting!). His commitment to teaching has been recognized with awards at UBC, including a Killam Teaching Prize. He has held significant leadership roles within the academic community, serving as General Chair for the 2023 ACM Conference on Economics and Computation (ACM-EC) and Program Co-Chair for AAAI 2021, one of the top two international AI conferences. He also chaired the ACM Special Interest Group on Economics and Computation and served as an Associate Editor for leading journals such as the Artificial Intelligence Journal (AIJ) and the Journal of Artificial Intelligence Research (JAIR).