Yu Li

Yu LI

ZJU100 Professor · School of Integrated Circuits, Zhejiang University

I work on the safety and reliability of AI-driven systems that interact with the physical world, with an emphasis on foundation and generative models (e.g., LLMs and video generation), and their reliable deployment in autonomous systems and digital twins for semiconductor manufacturing.

I received my Ph.D. from CUHK under Prof. Qiang Xu, and previously interned at IMEC, Alibaba Cloud, and Huawei Noah's Ark Lab. I received the Best Ph.D. Thesis Award from ATS 2022 and was selected as a KAUST AI Rising Star (2026).

🔬 I am looking for Postdoctoral Researchers with a strong background in AI security, autonomous systems, or EDA. Contact me at li.yu@zju.edu.cn.

I am also looking for self-motivated Ph.D. students, master students, and research assistants. Contact me at li.yu@zju.edu.cn or visit my Chinese website.

News

2026-03One paper is accepted to CVPR 2026.
2026-02I was selected as a KAUST AI Rising Star (2026).
2025-08Three papers are accepted to NeurIPS 2025.
2025-08Four papers are accepted to TDSC 2025, TIFS 2025, TCAD, and ASE 2025.
2025-05Check our paper on safety-critical driving dataset generation: website
2025-05Two papers have been accepted by ACL 2025. Congrats for all!
2025-05One paper has been accepted by ICML 2025. Congrats!
2025-01One paper has been accepted by ICLR 2025. Congrats, Linbao!
2024-12One paper has been accepted by AAAI 2025. Congrats, Zhiheng!
2024-09Two papers have been accepted by NeurIPS 2024!
2024-05One paper has been accepted to ICML'24.

Publications Full List →

Preprints

  • SafeMVDrive: Multi-view Safety-Critical Driving Video Synthesis in the Real World Domain
    Jiawei Zhou, Linye Lyu, Zhuotao Tian, Cheng Zhuo, Yu Li
    arXiv, 2025.
  • Toward Physically Consistent Driving Video World Models under Challenging Trajectories
    Jiawei Zhou, Zhenxin Zhu, Lingyi Du, Linye Lyu, Lijun Zhou, Zhanqian Wu, Hongcheng Luo, Zhuotao Tian, Bing Wang, Guang Chen, Hangjun Ye, Haiyang Sun, Yu Li
    arXiv, 2026.

2026

  • MaxMark: High-Capacity Diffusion-Native Watermarking via Robust and Invertible Latent Embedding
    Xuanhang Chang, Zhonghao Yang, Cheng Zhuo, Yu Li
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, CCF-A), 2026.

2025

  • SilentStriker: Toward Stealthy Bit-Flip Attacks on Large Language Models
    Haotian Xu, Qingsong Peng, Jie Shi, Huadi Zheng, Yu Li, Cheng Zhuo
    Conference on Neural Information Processing Systems (NeurIPS, CCF-A), 2025.
  • One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs
    Linbao Li, Yannan Liu, Daojing He, Yu Li
    International Conference on Learning Representations (ICLR, CCF-A), 2025.
  • DF-MIA: A Distribution-Free Membership Inference Attack on Fine-Tuned Large Language Models
    Zhiheng Huang, Yannan Liu, Daojing He, Yu Li
    AAAI Conference on Artificial Intelligence (AAAI, CCF-A), 2025.
  • MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming
    Weiyang Guo, Jing Li, Wenya Wang, Yu Li, Daojing He, Jun Yu, Min Zhang
    Annual Meeting of the Association for Computational Linguistics (ACL, CCF-A), 2025.
  • Function-to-Style Guidance of LLMs for Code Translation
    Longhui Zhang, Bin Wang, Jiahao Wang, Xiaofeng Zhao, Min Zhang, Hao Yang, Meishan Zhang, Yu Li, Jing Li, Jun Yu
    International Conference on Machine Learning (ICML, CCF-A), 2025.
  • FDTest: Prioritizing Test Inputs for Object Detection Models via Foundation Model Exploitation
    Chong Zhang, Qiuxia Lai, Yu Li
    International Joint Conference on Neural Networks (IJCNN, CCF-C), 2025.
  • ArcGen: Generalizing Neural Backdoor Detection Across Diverse Architectures
    Zhonghao Yang, Cheng Luo, Daojing He, Yiming Li, Yu Li
    IEEE Transactions on Information Forensics and Security (TIFS, CCF-A), 2025.
  • SPLAT: Revisiting Latency Attack on Dynamic Neural Networks
    Yu Li, Biao Huang, Jinyin Hu, Cheng Zhuo
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD, CCF-A), 2025.
  • Toward Efficient Quality Testing of Graph Neural Networks via Test Input Prioritization
    Lichen Yang, Qiang Wang, Zhonghao Yang, Daojing He, Yu Li
    Automated Software Engineering (ASE, CCF-B), 2025.
  • Toward Robust and Accurate Adversarial Camouflage Generation Against Vehicle Detectors
    Jiawei Zhou, Linye Lyu, Yu Li
    IEEE Transactions on Dependable and Secure Computing (TDSC, CCF-A), 2025.

2024

  • CNCA: Toward Customizable and Natural Generation of Adversarial Camouflage for Vehicle Detectors
    Linye Lyu, Jiawei Zhou, Daojing He, Yu Li
    Conference on Neural Information Processing Systems (NeurIPS, CCF-A), 2024.
  • Vector Quantization Prompting for Continual Learning
    Li Jiao, Qiuxia Lai, Yu Li, Qiang Xu
    Conference on Neural Information Processing Systems (NeurIPS, CCF-A), 2024.
  • RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
    Jiawei Zhou, Linye Lyu, Daojing He, Yu Li
    International Conference on Machine Learning (ICML, CCF-A), 2024.
  • Protecting Object Detection Models from Model Extraction Attack via Feature Space Coverage
    Zeyu Li, Yuwen Pu, Xuhong Zhang, Yu Li, Jinbao Li, Shouling Ji
    International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2024.
  • Enhancing Flow Embedding Through Trace: A Novel Self-supervised Approach for Encrypted Traffic Classification
    Zefei Luo, Yu Li, Shuaishuai Tan, Daojing He
    International Joint Conference on Neural Networks (IJCNN, CCF-C), 2024.
  • The Dawn of AI-Native EDA: Opportunities and Challenges of Large Circuit Models
    Lei Chen, ..., Yu Li, ..., Sunnan Zou
    SCIENCE CHINA Information Sciences (SCIS, CCF-A), 2024.
  • Spatial Attention for Human-Centric Visual Understanding: An Information Bottleneck Method
    Qiuxia Lai, Yongwei Nie, Yu Li, Hanqiu Sun, Qiang Xu
    Computer Vision and Image Understanding (CVIU, CCF-B), 2024.
  • A Novel Approach to Reducing Testing Costs and Minimizing Defect Escapes Using Dynamic Neighborhood Range and Shapley Values
    Tianming Ni, Wangsheng Rui, Cheng Zuo, Yu Li, Xiaoqing Wen, Mu Nie
    ACM Transactions on Design Automation of Electronic Systems (TODAES, CCF-B), 2024.
  • On Function-Coupled Watermarks for Deep Neural Networks
    Xiangyu Wen, Yu Li, Wei Jiang, Qiang Xu
    IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS, JCR-Q2), 2024.

2023

  • HiBug: On Human-Interpretable Model Debug
    Muxi Chen, Yu Li, Qiang Xu
    Conference on Neural Information Processing Systems (NeurIPS, CCF-A), 2023.
  • EXPERT: Exploiting DRAM Error Types to Improve the Effective Forecasting Coverage in the Field
    Xiangjun Peng, Zheng Huang, Alex Cantrell, Bihua Shu, Ke Ke Xie, Yi Li, Yu Li, Li Jiang, Qiang Xu, Ming-Chang Yang
    IEEE/IFIP International Conference on Dependable Systems and Networks (DSN, CCF-B), 2023.
  • Towards Robust Deep Neural Networks Against Design-Time and Run-Time Failures
    Yu Li, Qiang Xu
    International Test Conference (ITC, CCF-B), 2023.
  • Self-Supervised Video Representation Learning via Capturing Semantic Changes Indicated by Saccades
    Qiuxia Lai, Ailing Zeng, Ye Wang, Lihong Cao, Yu Li, Qiang Xu
    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT, CCF-B), 2023.

2022

  • What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
    Yijun Yang, Ruiyuan Gao, Yu Li, Qiuxia Lai, Qiang Xu
    Network and Distributed System Security Symposium (NDSS, CCF-A), 2022.
  • HybridRepair: Towards Annotation-Efficient Repair for Deep Learning Models
    Yu Li, Muxi Chen, Qiang Xu
    ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA, CCF-A), 2022.

2021

  • TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks
    Yu Li, Min Li, Qiuxia Lai, Yannan Liu, Qiang Xu
    Conference on Neural Information Processing Systems (NeurIPS, CCF-A), 2021.
  • Information Bottleneck Approach to Spatial Attention Learning
    Qiuxia Lai, Yu Li, Ailing Zeng, Minhao Liu, Hanqiu Sun, Qiang Xu
    International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2021.
  • AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference
    Min Li, Yu Li, Ye Tian, Li Jiang, Qiang Xu
    Design Automation Conference (DAC, CCF-A), 2021.
  • On Workload-Aware DRAM Failure Prediction in Large-Scale Data Centers
    Xingyi Wang, Yu Li, Yiquan Chen, et al.
    IEEE VLSI Test Symposium (VTS, CCF-C), 2021.

2020

  • DeepDyve: Dynamic Verification for Deep Neural Networks
    Yu Li, Min Li, Bo Luo, Ye Tian, Qiang Xu
    ACM SIGSAC Conference on Computer and Communications Security (CCS, CCF-A), 2020.
  • On Configurable Defense against Adversarial Example Attacks
    Bo Luo, Min Li, Yu Li, Qiang Xu
    Great Lakes Symposium on VLSI (GLSVLSI, CCF-C), 2020.

2019

  • D2NN: A Fine-Grained Dual Modular Redundancy Framework for Deep Neural Networks
    Yu Li, Yannan Liu, Min Li, Ye Tian, Bo Luo, Qiang Xu
    Annual Computer Security Applications Conference (ACSAC, CCF-B), 2019.
  • On Functional Test Generation for Deep Neural Network IPs
    Bo Luo, Yu Li, Lingxiao Wei, Qiang Xu
    Design, Automation & Test in Europe Conference (DATE, CCF-B), 2019.

2018

  • I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators
    Lingxiao Wei, Yannan Liu, Bo Luo, Yu Li, Qiang Xu
    Annual Computer Security Applications Conference (ACSAC, CCF-B), 2018.
  • IEEE Std P1838's Flexible Parallel Port and its Specification with Google's Protocol Buffers
    Yu Li, Ming Shao, Hailong Jiao, Adam Cron, Sandeep Bhatia, Erik Jan Marinissen
    IEEE European Test Symposium (ETS, CCF-C), 2018.

Teaching

  • COMP5034System Security, 2023 Fall
  • COMP3054Computers and Network Security, 2023 Spring
  • CSCI3250Computers and Society (with Prof. CHAU Chuck-jee)
  • CENG2400Embedded System Design (with Prof. Qiang Xu)
  • ENGG1100Introduction to Engineering Design (with Prof. Anthony SUM)