Li Wenjie(李文杰)

Li Wenjie(李文杰)

Hebei Normal University

Li Wenjie received the Ph.D. degree from Xidian University in 2025. He is currently a Lecturer with the School of Computer and Cyber Security, Hebei Normal University. His research interests include federated (un)learning and trustworthy artificial intelligence. From 2023 to 2024, he was a visiting student at the College of Computing and Data Science (CCDS), Nanyang Technological University, Singapore. He has published some papers with .

📖 Educations

  • 2023.11 - 2024.10, Visiting Ph.D. Student, College of Computing and Data Science, Nanyang Technological University, Supervised by Wei Yang Bryan Lim.

  • 2021.09 - 2025.06, Ph.D. in Cybersecurity, School of Network and Information Security, Xidian University, Supervised by Fan Kai.

  • 2018.09 - 2021.06, Master of Cybersecurity, School of Cybersecurity and Computer Science, Hebei University, Supervised by Yang Xiaohui.

  • 2014.09 - 2018.06, Bachelor of Network Engineering, School of Cybersecurity and Computer Science, Hebei University.

💡 Research directions

  • (un)federated learning
  • Trustworthy and adversarially-robust machine learning
  • Applied cryptography (e.g., Zero-Knowledge Proofs, Secure Multi-Party Computation) for machine-learning systems

🎖 Research Grants

  • Science Foundation of Hebei Normal University (L2026B33)
  • Hebei Natural Science Foundation (F2026205020)

📝 Publications

[1]
Zhang Fuyao, Zhang Jiaming, Wang Che, Sun Xiongtao, Hao Yurong, Guan Guowei, Li Wenjie, Huang Longtao, Lim Wei Yang Bryan. DualTAP: A Dual-Task Adversarial Protector for Mobile MLLM Agents[C]//ECCV. 2026. DOI:10.48550/arXiv.2511.13248.
[2]
Fan Kai, Wang Huixuan, Li Wenjie, Li Xiang, Li Hui, Zhang Kuan, Yang Yintang, Wang Lianhai. NeuDFL: Efficient neuron-based defense against label flipping attacks on non-IID data[J]. IEEE Internet of Things Journal, 2026, 13(12): 26599-26607. DOI:10.1109/JIOT.2026.3676632.
[3]
Zhang Pingle, Fan Kai, Li Xiang, Li Wenjie, Zhang Kuan, Li Hui, Yang Yintang, Wang Lianhai. HBA: Hijacking-based backdoor attack for vertical federated learning[J]. IEEE Internet of Things Journal, 2026: 1-1. DOI:10.1109/JIOT.2026.3702700.
[4]
Zhang Fuyao, Yan Xinyu, Wu Tiantong, Li Wenjie, Chen Tianxiang, Cao Yang, Yan Ran, Huang Longtao, Lim Wei Yang Bryan, Yang Qiang. Oblivionis: A Lightweight Learning and Unlearning Framework for Federated Large Language Models[C]//Proceedings of the AAAI Conference on Artificial Intelligence: Vol. 40. 2026: 28185-28193. DOI:10.1609/aaai.v40i33.40045.
[5]
Li Wenjie, Fan Kai, Zhang Jingyuan, Li Hui, Lim Wei Yang Bryan, Yang Qiang. Enhancing security and privacy in federated learning using low-dimensional update representation and proximity based defense[J]. IEEE Transactions on Knowledge and Data Engineering, 2025. DOI:10.1109/TKDE.2025.3539717.
[6]
Li Wenjie, Fan Kai, Yang Kan, Yang Yintang, Li Hui. PBFL: Privacy-preserving and byzantine-robust federated-learning-empowered industry 4.0[J]. IEEE Internet of Things Journal, 2024, 11(4): 7128-7140. DOI:10.1109/JIOT.2023.3315226.
[7]
Fan Kai, Hong Jingtao, Li Wenjie, Zhao Xingwen, Li Hui, Yang Yintang. FLSG: A novel defense strategy against inference attacks in vertical federated learning[J]. IEEE Internet of Things Journal, 2024, 11(2): 1816-1826. DOI:10.1109/JIOT.2023.3302792.
[8]
Yang Xiaohui, Li Wenjie, Fan Kai. A revocable attribute-based encryption EHR sharing scheme with multiple authorities in blockchain[J]. Peer-to-Peer Networking and Applications, 2023, 16(1): 107-125. DOI:10.1007/s12083-022-01387-4.
[9]
Yang Xiaohui, Li Wenjie. A zero-knowledge-proof-based digital identity management scheme in blockchain[J]. Computers & Security, 2020, 99: 102050. DOI:https://doi.org/10.1016/j.cose.2020.102050.

🎓 Prospective Students

I am actively looking for motivated M.Sc. students to join my group at the School of Computer and Cyber Security, Hebei Normal University. If you have a strong interest in cyber security research, please get in touch.

  • Solid programming skills in Python with hands-on experience building and training models in PyTorch
  • Familiarity with deep learning models (e.g., CNNs, Transformers, federated learning frameworks)
  • Genuine research interest in cyber security, privacy, or trustworthy AI
  • Self-driven, comfortable reading and discussing recent papers in English, and willing to do rigorous empirical work

Please email me at liwenjie@hebtu.edu.cn with your CV / résumé and a short paragraph describing your research interests and any prior projects