Paper 'Taming “data-hungry” reinforcement learning? Stability in continuous state-action spaces' posted on arXiv in January 2024 and accepted by NeurIPS 2024; Paper 'Optimal policy evaluation using kernel-based temporal difference methods' accepted by the Annals of Statistics in May 2024; Received first NSF grant in August 2024; Paper 'Adaptive and robust multi-task learning' accepted by the Annals of Statistics in December 2023; Honored with the 2023 IMS Lawrence D. Brown Ph.D. Student Award in October 2022; Delivered multiple talks at academic seminars and conferences.
Research Experience
Postdoctoral researcher at the Laboratory for Information & Decision Systems at MIT from 2022 to 2023; Joined NYU Stern School of Business as an Assistant Professor in the Department of Technology, Operations, and Statistics in August 2023.
Education
Ph.D. from the Department of Operations Research and Financial Engineering at Princeton University in 2022; Postdoctoral researcher at the Laboratory for Information & Decision Systems at MIT from 2022 to 2023, working with Professor Martin J. Wainwright; B.S. in Mathematics from Peking University.
Background
Primary research interests: Machine learning, particularly statistical aspects of reinforcement learning. Profile: Assistant Professor in the Department of Technology, Operations, and Statistics at Stern School of Business, New York University.