Greetings and Welcome to My Homepage

Biography

I am currently a Research Fellow at Nanyang Technological University, working with Prof. Tianwei Zhang and Prof. Dacheng Tao. Prior to this, I was a Research Professor (similar to a Tenure-track Associate Professor in the U.S.) in the research group led by Prof. Zhan Qin and Prof. Kui Ren at Zhejiang University, where I received the Outstanding Junior Faculty Award (Qizhen Outstanding Young Scholar) and held appointments at both the State Key Laboratory of Blockchain and Data Security and HIC-ZJU. 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, and my B.S. degree with honors in Mathematics from Ningbo University (Yangming Innovation Class), where I was advised by Prof. Lifeng Xi. I also collaborated closely with Dr. Zhifeng Li (Tencent) and Prof. Bo Li (UIUC) during my Ph.D. journey.

My research mainly focuses on Trustworthy ML and Responsible AI, especially AI Risk Management and AI Copyright Protection. My long-term goal is to make AI-based systems more secure and copyright-preserving during their full life cycle. Recently, I focus more on Trustworthy Generative AI (e.g., LLMs, Diffusion Models, and AI Agents). I always chase for simple yet effective methods with deep insights and theoretical support.

For Potential Students and Collaborators: 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!

Selected Research

(Generative) AI has achieved remarkable progress and widespread adoption, yet ensuring its sustainable development remains a critical challenge. This calls for integrating risk management to enable trustworthy large-scale deployment and copyright protection to promote innovation and fair competition. In general, my research advances a sustainable AI ecosystem by systematically unifying these two dimensions, as outlined below:

• AI Risk Management
  • Risk Sensing: [USENIX Security’25, S&P’25, ICLR’25, TIFS’25, TDSC’25, CVPR’24, TIFS’24 (a), ICCV’23, TIFS’24 (b), ICLR’23, AAAI’23, PR’23, ICLR’22, ICASSP’21, ICCV’21, ICLR’21, ECCV’20 (Oral)]
  • Risk Mitigation: [ICLR’25 (a), ICLR’25 (b), ICML’25, ACL’25 (a), ACL’25 (b), ICML’24 (a), ICML’24 (b), CVPR’25, ICLR’24 (a) (Spotlight), ICLR’24 (b), IJCAI’24, IJCV’24, NeurIPS’23, ICLR’23, ICLR’22, PR’22]
• AI Copyright Protection
  • Data(set) Copyright: [USENIX Security’25, S&P’25 (a), S&P’25 (b), NeurIPS’24, TIFS’24, TIFS’23 (TOP-25 Papers), NeurIPS’23, PR’22, NeurIPS’22 (Oral)]
  • Model Copyright: [NDSS’25, CVPR’25, ICLR’25, TPAMI’25, ECCV’24, ICCV’23, AAAI’22]

News

• 08/2025: I am invited to serve as the Area Chair for ICLR 2026.
• 08/2025: I will serve as the Consulting Area Editor for IEEE TIFS.
• 07/2025: One paper about backdoor defense is accepted by IEEE TIFS.
• 05/2025: Two papers about LLM Safety and Security are accepted by ACL (Main Track) 2025.
• 04/2025: I am invited to serve as the Area Chair for NeurIPS 2025.

Useful Resources

Perspective: Rethinking Data Protection in the (Generative) Artificial Intelligence Era

Survey and Benchmark for Fingerprinting-based LLM's Copyright Auditing, as well as its Toolbox

Survey and Benchmark for for Dataset Auditing, as well as its Toolbox

Survey, Toolbox, and GitHub Resources Repo about Backdoor Learning.

A Brief Bio: Dr. Yiming Li is currently a Research Fellow at Nanyang Technological University. Prior to this, he was a Research Professor at Zhejiang University, where he received the Outstanding Junior Faculty Award and held appointments at both the State Key Laboratory of Blockchain and Data Security and HIC-ZJU. He obtained his Ph.D. in Computer Science and Technology (with honors) from Tsinghua University and his B.S. in Mathematics (with honors) from Ningbo University. His research centers on Trustworthy Machine Learning and Responsible Artificial Intelligence, with a particular focus on AI Safety, AI Security, and AI Copyright Protection. His work has been published in leading venues, such as IEEE S&P, USENIX Security, NDSS, ICML, NeurIPS, ICLR, CVPR, ICCV, IEEE TPAMI, and IEEE TIFS. Dr. Li serves as an Associate Editor for Pattern Recognition, Consulting Area Editor for IEEE TIFS, Area Chair for ICLR, NeurIPS, ICML, and ACM Multimedia, and Senior Program Committee Member for AAAI and IJCAI. He also regularly reviews for leading journals such as IEEE TPAMI, IJCV, IEEE TIFS, and IEEE TDSC. His research has been featured in major media outlets, including IEEE Spectrum and MIT Technology Review. He is the recipient of several prestigious honors, such as the Best Paper Award at PAKDD, the Rising Star Award at WAIC, the KAUST Rising Stars in AI, and the DAAD AInet Fellowship.