Professor Wee Sun Lee is a distinguished computer scientist and leading authority in machine learning theory and planning under uncertainty at the National University of Singapore. He currently serves as a Full Professor in the Department of Computer Science, where he has held significant leadership positions including Head of the Department of Computer Science, Vice Dean of Undergraduate Studies, and Vice Dean of Research at the National University of Singapore. He earned his B.Eng. in Computer Systems Engineering from the University of Queensland in 1992 and completed his Ph.D. at the Australian National University in 1996 with a thesis on agnostic learning and neural networks under Peter Bartlett and Robert Williamson. Prior to his current position, he served as a research fellow at the Australian Defence Force Academy, a fellow of the Singapore-MIT Alliance, and a visiting scientist at MIT, establishing a strong foundation in both theoretical and applied computer science.
Dr. Lee's research program focuses on fundamental questions in machine learning theory, planning under uncertainty, and approximate inference, with numerous contributions that have shaped contemporary approaches in these areas. His seminal work on Forward Pruning in Game-Tree Search, particularly the RankCut algorithm developed with his student Yew Jin Lim, has influenced subsequent developments in search algorithms. His publication record includes influential papers such as Monte Carlo Value Iteration for Continuous-State POMDPs from 2010, Bootstrapping Monte Carlo Tree Search with an Imperfect Heuristic from 2012, and Shortest Path under Uncertainty from 2017, which have advanced methodologies for decision-making under uncertainty. This body of work demonstrates his unique ability to bridge theoretical computer science with practical applications in artificial intelligence, creating rigorous frameworks that have become foundational in several subfields.
Beyond his research contributions, Professor Lee has earned significant recognition including the Test of Time Award at Robotics: Science and Systems from 2021, the RoboCup Best Paper Award at IROS from 2015, the Google Best Student Paper Award at UAI from 2014, and the IJCAI-JAIR Best Paper Prize from 2022. He has served as an area chair for premier conferences including NeurIPS, ICML, AAAI, and IJCAI, demonstrating his leadership in the global AI research community. His role as co-chair of the steering committee for the Asian Conference on Machine Learning further underscores his commitment to advancing the field in the Asia-Pacific region. Currently, Professor Lee continues to guide the next generation of researchers while pushing the boundaries of machine learning theory and its applications to complex real-world problems requiring decision-making under uncertainty.
