David HSU
Provost's Chair ProfessorDirector, Smart Systems Institute
- Ph.D. (Computer Science, Stanford University)
- B.Sc. (Computer science & Mathematics, University of British Columbia)
David Hsu is Provost’s Chair Professor in the Department of Computer Science, the founding director of NUS Artificial Intelligence Laboratory (NUSAIL), and the director of Smart Systems Institute. He received a BSc in computer science & mathematics from the University of British Columbia, Canada and PhD in computer science from Stanford University, USA. He is an IEEE Fellow. His research spans robotics, AI, and computational biology. In recent years, he has been working on robot planning and learning under uncertainty and human-robot collaboration. He has chaired and co-chaired several major international robotics conferences, including International Workshop on the Algorithmic Foundation of Robotics (WAFR) 2004 and 2010, Robotics: Science & Systems 2015, IEEE International Conference on Robotics & Automation (ICRA) 2016, and Conference on Robot Learning (CoRL) 2021. He was an associate editor of IEEE Transactions on Robotics. He is currently serving on the editorial board of Journal of Artificial Intelligence Research and the RSS Foundation Board.
RESEARCH AREAS
Artificial Intelligence
- Decision Making & Planning
- Machine Learning
- Robotics
RESEARCH INTERESTS
Robotics
Artificial Intelligence
Robot Planning & Learning
Decision-Making under Uncertainty
Human-Robot Collaboration
RESEARCH PROJECTS
RESEARCH GROUPS
Adaptive Computing Laboratory
Our long-term goal is to understand the fundamental computational questions that enable fluid human-robot interaction, collaboration, and ultimately co-existence. Our current research focuses on robust robot decision-making under uncertainty by integrating planning and machine learning.
TEACHING INNOVATIONS
SELECTED PUBLICATIONS
- X. Ma, P. Karkus, D. Hsu, and W.S. Lee. Particle filter recurrent neural networks. In Proc. AAAI Conf. on Artificial Intelligence, 2020.
- X. Ma, P. Karkus, D. Hsu, W.S. Lee, and N. Ye. Discriminative particle filter reinforcement learning for complex partial observations. In Proc. Int. Conf. on Learning Representations, 2020.
- P.P. Cai, Y.F. Luo, A. Saxena, D. Hsu, and W.S. Lee. LeTS-Drive: Driving in a crowd by learning from tree search. In Proc. Robotics: Science & Systems, 2019.
- P. Karkus, X. Ma, D. Hsu, L.P. Kaelbling, W.S. Lee, and T. Lozano-Perez. Differentiable algorithm networks for composable robot learning. In Proc. Robotics: Science & Systems, 2019.
- M. Shridhar and D. Hsu. Interactive visual grounding of referring expressions for human-robot interaction. In Proc. Robotics: Science & Systems, 2018.
- P. Karkus, D. Hsu, and W.S. Lee. QMDP-Net: Deep learning for planning under partial observability.Advances in Neural Information Processing Systems, 2017.
- Z. Lan, M. Shridhar, D. Hsu, and S. Zhao.XPose: Reinventing user interaction with flying cameras. InProc. Robotics:Science & Systems, 2017.
- A. Kupcsik, D. Hsu, and W.S. Lee.Learning dynamic robot-to-human object handover from human feedback. InProc.Int. Symp. on Robotics Research, 2015.
- H.Y. Bai, S.J. Cai, N. Ye, D. Hsu, and W.S. Lee.Intention-aware online POMDP planning for autonomous driving in acrowd. InProc. IEEE Int. Conf. on Robotics & Automation, 2015.
- A. Somani, N. Ye, D. Hsu, and W. Lee. DESPOT: Online POMDP planning with regularization. In Advances in Neural Information Processing Systems. 2013.
AWARDS & HONOURS
IJCAI-JAIR Best Paper Prize, 2022
Test of Time Award, Robotics: Science & Systems (RSS), 2021
IEEE Fellow, 2018
Best Systems Paper Award, Robotics: Science & Systems (RSS), 2017
RoboCup Best Paper Award, IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS), 2015.
Humanitarian Robotics and Automation Technology Challenge Award, IEEE International Conference on Robotics & Automation (ICRA), 2015.
MODULES TAUGHT