Greetings and Welcome to My Homepage


I am currently a Research Professor (HIC-ZJU-100 Young Professor, ZJU Qizhen Outstanding Young Scholar) in the State Key Laboratory of Blockchain and Data Security at Zhejiang University and also in HIC-ZJU, working closely with Prof. Zhan Qin and Prof. Kui Ren. Before that, I received my Ph.D. degree with honors in Computer Science and Technology from Tsinghua University, advised by Prof. Yong Jiang and Prof. Shu-Tao Xia. I received my B.S. degree with honors in Mathematics from Ningbo University, advised by Prof. Lifeng Xi. I also collaborated closely with Dr. Zhifeng Li (from Tencent) and Prof. Bo Li (from UIUC) during my Ph.D. journey.

My research mainly focuses on Trustworthy ML and Responsible AI, especially backdoor attacks/defenses and copyright protection in deep learning. My long-term goal is to make DNNs more secure and copyright-preserving during their full life cycle. Recently, I focus more on Trustworthy Large Foundation Models (e.g., GPT and Diffusion Model). I always chase for simple yet effective methods with deep insights and theoretical support.


I am always looking for highly self-motivated students and research interns to join exciting research projects on Trustworthy ML and Responsible AI in our group. I will provide responsible and hands on guidance. Besides, I am always willing to work together on interesting projects with external collaborators. Drop me an email if you are interested!


  • 04/2024: So glad and humble to become the DAAD AInet Fellow (on Safety and Security in AI).
  • 03/2024: So glad and humble to receive the Outstanding Doctoral Dissertation Award from SZCCF.
  • 02/2024: Two papers about backdoor learning (1 backdoor attack against ViT and 1 backdoor defense) are accepted by CVPR. Congrats and thanks to Boheng Li, Sheng Yang, Jiawang Bai, and all collaborators! Their codes will be released soon.
  • 01/2024: I am invited as an Area Chair of ACM MM 2024.
  • 01/2024: So glad and humble to become the Qizhen Outstanding Young Scholar at Zhejiang University.

Useful Resources

BackdoorBox: A Python Toolbox for Backdoor Attacks and Defenses

Github Repo about Backdoor Learning Resources