Dr. Wenbo Jiang is currently a postdoctoral (associate researcher fellow) in the School of Computer Science and Engineering (School of Cyberspace Security) at the University of Electronic Science and Technology of China, under the supervision of Prof. Hongwei Li (IEEE Fellow). Dr. Jiang was awarded for the National Postdoctoral Innovative Talent Support Program in 2023, and obtained youth program of the National Natural Science Foundation of China in 2024. As the first/corresponding author, he has published many papers in major conferences/journals, including USENIX Security、CCS、IEEE CVPR、AAAI、ICML、IEEE TDSC、IEEE TIFS, etc.

Email: wenbo_jiang@uestc.edu.cn

Research interests

AI security and Privacy; Trustworthy AI; Backdoor attacks; Adversarial attacks; Data security

Education

2013-2017: Bachelor degree in Cyber Security, University of Electronic Science and Technology of China.
2017-2019: Master degree in Cyber Security, University of Electronic Science and Technology of China.
2021-2022: Visiting PhD in Cyber Security, Nanyang Technological University (supervised by Prof. Tianwei Zhang).
2019-2023: PhD degree in Cyber Security, University of Electronic Science and Technology of China (supervised by Prof. Hongwei Li).

Academic service

Reviewer for conference: NIPS 2025, KDD 2025, ICCV 2025, CLOM 2025, CVPR 2025, ICLR 2025, ICME 2025, ICASSP 2025, IJCNN 2025 (Area Chair), BMVC 2025 (Area Chair) etc.

Reviewer for journals: IEEE TIFS, IEEE TDSC, IEEE TCSVT, IEEE IoTJ, IEEE TNNLS, IEEE TAI, IEEE TVT, ACM TOIT, etc.

Guest editor: A special issue of Electronics (Security and Privacy for AI) https://www.mdpi.com/journal/electronics/special_issues/F996X09SVU

Selected publications

• Rui Zhang, Yun Shen, Hongwei Li, Wenbo Jiang, Hanxiao Chen, Yuan Zhang, Guowen Xu, Yang Zhang. The Ripple Effect: On Unforeseen Complications of Backdoor Attacks. International Conference on Machine Learning (ICML), 2025.
  
• Shuai Yuan, Hongwei Li, Rui Zhang, Hangcheng Cao, Wenbo Jiang, Tao Ni, Wenshu Fan, Qingchuan Zhao, Guowen Xu. Omni-Angle Assault: An Invisible and Powerful Physical Adversarial Attack on Face Recognition. International Conference on Machine Learning (ICML), 2025.
  
• Wenshu Fan, Minxing Zhang, Hongwei Li, Wenbo Jiang*, Hanxiao Chen, Xiangyu Yue, Michael Backes, Xiao Zhang, “DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy”, in Proceedings of ACM SIGSAC Conference on Computer and Communications Security (CCS), 2025.
  
• Wenbo Jiang, Hongwei Li, Guowen Xu, Hao Ren, Haomiao Yang, Tianwei Zhang, Shui Yu, “Rethinking the Design of Backdoor Triggers and Adversarial Perturbations: A Color Space Perspective” in IEEE Transactions on Dependable and Secure Computing, DOI: 10.1109/TDSC.2024.3521942.
  
• Jiaming He, Wenbo Jiang*, Guanyu Hou, Wenshu Fan, Rui Zhang and Hongwei Li. “ Watch Out for Your Guidance on Generation! Exploring Conditional Backdoor Attacks against Large Language Models.” Proceedings of the AAAI 2025.
  
• Wenbo Jiang, H. Li, G. Xu, T. Zhang, “Color backdoor: A robust poisoning attack in color space” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 8133-8142.
  
• Wenbo Jiang, H. Li, G. Xu, T. Zhang and R. Lu, “A Comprehensive Defense Framework Against Model Extraction Attacks,” in IEEE Transactions on Dependable and Secure Computing, vol. 21, no. 2, pp. 685-700, March-April 2024, doi: 10.1109/TDSC.2023.3261327.
  
• W. Fan, H. Li, Wenbo Jiang*, M. Hao, S. Yu and X. Zhang, “Stealthy Targeted Backdoor Attacks Against Image Captioning,” in IEEE Transactions on Information Forensics and Security, vol. 19, pp. 5655-5667, 2024, doi: 10.1109/TIFS.2024.3402179.
  
• R. Zhang, H. Li, R. Wen, Wenbo Jiang, Y. Zhang, M. Backes, Y. Shen and Y. Zhang, “Instruction backdoor attacks against customized {LLMs},” In 33rd USENIX Security Symposium (USENIX Security 24) (pp. 1849-1866).
  
• Wenbo Jiang, T. Zhang, H. Qiu, H. Li and G. Xu, “Incremental Learning, Incremental Backdoor Threats,” in IEEE Transactions on Dependable and Secure Computing, vol. 21, no. 2, pp. 559-572, March-April 2024, doi: 10.1109/TDSC.2022.3201234.
  

Google scholar: https://scholar.google.com/citations?user=OjHzvJkAAAAJ