I am an incoming Assistant Professor at Department of Computer Science and Engineering, University of California, Riverside (starting in July, 2025). I completed Ph.D. at UCLA Computer Science Department in 2025, advised by Prof. Cho-Jui Hsieh. I received my B.Eng. degree from the CST department at Tsinghua University in 2020.
My primary research focus is on trustworthy machine learning, and I am broadly interested in developing more trustworthy and reliable AI models. In particular, I work on verifiable machine learning, with topics such as formal verification for neural networks, training verification-friendly neural networks with stronger verifiable guarantees, applications of verifiable machine learning in mission-critical scenarios, and more recently, the interplay between verifiers and generative AI. Additionally, I also study empirical methods for evaluating and improving the robustness or safety of large-scale ML foundation models.
🎓 Prospective Students: I am looking for motivated students to join my group, including PhD students to start in the 2025~2026 academic year and interns. For interested students, please reach out by email with a brief description of research interests, CV, and transcript.
Selected Publications (* Equal contribution)
Awards
- UCLA Dissertation Year Award (fellowship), 2024-2025
- Amazon Fellowship (Amazon & UCLA Science Hub fellowship), 2022-2023
- 4X first-place winner at the International Verification of Neural Networks Competition (VNN-COMP), 2021-2024
Teaching
Upcoming at UCR:
- Fall 2025: CS 260 Seminar in Computer Science - Trustworthy AI
TA at UCLA:
- CS 35L Software Construction (Fall 2023; Spring 2022)
- CS M146 Introduction to Machine Learning (Fall 2022)
- CS 260C Deep Learning (Winter 2022)