About me

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; for full publications: see Publications or Google Scholar )
Neural Network Verification with Branch-and-Bound for General Nonlinearities
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
Defending LLMs against Jailbreaking Attacks via Backtranslation
Red Teaming Language Model Detectors with Language Models
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
Fast Certified Robust Training with Short Warmup
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

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)