- D(RO) Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping, won Best Robotics Paper Award at CoRL 2024 MAPoDeL Workshop.
- Improving Offline Reinforcement Learning with Inaccurate Simulators, presented at ICRA 2024.
- Effective Offline Robot Learning with Structured Task Graph, published in IEEE Robotics and Automation Letters (RA-L) 2024.
Research Experience
Involved in multiple research projects including D(RO) Grasp, improving offline reinforcement learning with inaccurate simulators, and effective offline robot learning with structured task graphs.
Education
Ph.D. student at School of Computing, National University of Singapore, advised by Prof. Lin Shao; Master's and Bachelor's degrees from the School of Computer Science and Technology, University of Science and Technology of China, advised by Prof. Feng Wu.
Background
Research Interests: Reinforcement learning and robotics, particularly offline reinforcement learning; interested in sim-to-real transfer and applications in real-world robotic tasks.
Miscellany
The website is designed based on Jon Barron's website. Last Update: Dec, 2024.