Published multiple papers including 'LodeStar: Long-horizon Dexterity via Synthetic Data Augmentation from Human Demonstrations' (CoRL 2025), 'RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning' (RSS 2025), etc.; Involved in the project 'UniDexGrasp++' which was a Best Paper Finalist at ICCV 2023; 1st place winner of SAPIEN ManiSkill Challenge 2021 (ICLR 2022 Challenge Track).
Research Experience
Currently a research intern at NVIDIA Seattle Robotics Lab; Previously, did research internship at NVIDIA GEAR (Spring 2024); Was a Visiting Student at CMU (Spring 2023) and UT Austin (Summer 2023).
Education
Currently a Ph.D. student in CSE at UCSD, advised by Prof. Hao Su; Obtained B.S. of Computer Science from Peking University with honor.
Background
Research interests lie at the intersection of Machine Learning, Robotics, and Computer Vision. Particularly interested in developing methods to generate and learn from diverse data for robots, enabling effective learning from minimal human supervision.
Miscellany
Feel free to contact me if you want to discuss or collaborate!