I am a final-year Ph.D. Candidate in the Department of Computer Science at University of California, Los Angeles. I have been fortunate to be advised by Prof. Quanquan Gu. Previously I obtained my B.E. form Department of Automation, Tsinghua University and M.Sc. during my Ph.D. career.
My research interests are the optimization and machine learning, especially the Reinforcement Learning. I’m interested in discovering the theory of Reinforcement Learning and designing the provably data-efficient algorithm with the application towards real-world problem. Also, I’m quite interested in AI4science, especially using machine learning to understand the fundamental science (quantum mechanics or chemistry) problems. You can findmy latest CV here
I’m on the academia job market for year 2024 now. Feel free to reach out to me if you are interested in my research / projects!
Latest Update @ 2023-06
- [2023-06] It is my great fortune to have been awarded the UCLA Dissertation Year Fellowship!
- [2023-06] I’m delighted to be returning to Nvidia as an intern and have the opportunity to work with Dr. Xiaoyun Wang and Dr. Joe Eaton, Dr. Weili Nie and Dr. Bradley Rees again this summer!
- [2022-09] It’s my great pleasure to work as a summer intern at Nvidia with Dr. Xiaoyun Wang and Dr. Bradley Rees. I’m also fortunate to receiving the guidance with the guidance from Dr. Joe Eaton during my summer internship.
- [2022-04] I’ve passed my Oral Qualification Exam and advanced to candidate. You can find my oral slides here. Thanks a lot for the suggestions and guidance of my Ph.D. committee members!
- [2021-12] I am really excited to be awarded the Amazon science hub fellowship and be known as an Amazon Fellow.
- [2020-06] Our project Combating COVID-19 has been adopted in the COVID-19 Forecasts by Centers for Disease Control and Prevention (CDC), California COVID Assessment Tool (CalCat) by California Department of Public Health (CDPH), and the COVID-19 Forecast Hub by the Reich Lab of the University of Massachusetts Amherst.