🆔 About Me

I am a Ph.D. candidate at Tongji University, advised by Prof. Guanjun Liu. I was a visiting student at the New Jersey Institute of Technology, advised by Prof. MengChu Zhou.

My research interests include multi-agent systems, reinforcement learning, and trustworthy AI, as well as their applications (e.g., autonomous UAV collaboration).

📝 Publications

Z.Y. Zhou, G.J. Liu, M.C. Zhou, W.R. Guo, Robust multi-agent reinforcement learning with stochastic adversary, 42nd International Conference on Machine Learning (ICML 2025). (Accepted)
Z.Y. Zhou, G.J. Liu, Robustness Testing for Multi-Agent Reinforcement Learning: State Perturbations on Critical Agents, 26th European Conference on Artificial Intelligence (ECAI 2023).
Z.Y. Zhou, G.J. Liu, M.C. Zhou,A robust mean-field actor-critic reinforcement learning against adversarial perturbations on agent states, IEEE Transactions on Neural Networks and Learning Systems, 2023.
Z.Y. Zhou, G.J. Liu, W.R. Guo, M.C. Zhou, Adversarial Attacks on Multiagent Deep Reinforcement Learning Models in Continuous Action Space, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024.
Z.Y. Zhou, G.J. Liu, Y. Tang, Multiagent Reinforcement Learning: Methods, Trustworthiness, Applications in Intelligent Vehicles, and Challenges, IEEE Transactions on Intelligent Vehicles, 2024.
W.R. Guo, G.J. Liu, Z.Y. Zhou, L. Wang, PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning, 34th International Joint Conference on Artificial Intelligence (IJCAI 2025). (Accepted)
W.R. Guo, G.J. Liu, Z.Y. Zhou, J.C. Wang, Y. Tang, M.M. Wang, Robust Training in Multi-agent Deep Reinforcement Learning against Optimal Adversary, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025.
H.R. Shi, G.J. Liu, K.W. Zhang, Z.Y. Zhou, J.C. Wang, MARL Sim2Real transfer: Merging physical reality with digital virtuality in metaverse, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023.
S.T. Chen, G.J. Liu, Z.Y. Zhou, K.W. Zhang, J.C. Wang, Robust multi-agent reinforcement learning method based on adversarial domain randomization for real-world dual-uav cooperation, IEEE Transactions on Intelligent Vehicles, 2024.
J. Xue, Z.N. Liu, G.J. Liu, Z.Y. Zhou, K.W. Zhang, Y. Tang, J.C. Wang, Robust wind-resistant hovering control of quadrotor UAVs using deep reinforcement learning, IEEE Transactions on Intelligent Vehicles, 2024.
M. Yang, G.J. Liu, Z.Y. Zhou, J.C. Wang, Probabilistic Automata-based Method for Enhancing Performance of Deep Reinforcement Learning Systems, IEEE/CAA Journal of Automatica Sinica, 2024.
W.R. Guo, G.J. Liu, Z.Y. Zhou, L. Wang, J.C. Wang, Enhancing the robustness of qmix against state-adversarial attacks, Neurocomputing, 2024.
M. Yang, G.J. Liu, Z.Y. Zhou, J.C. Wang, Partially observable mean field multi-agent reinforcement learning based on graph attention network for UAV swarms, Drones, 2023.
P. Zhou, G.J. Liu, J.C. Wang, Q.L. Weng, K.W. Zhang, Z.Y. Zhou, Lightweight unmanned aerial vehicle video object detection based on spatial-temporal correlation, International Journal of Communication Systems, 2022.

📖 Educations

Sep. 2020 – Mar. 2026 (expected), Tongji University

Ph.D. Candidate in Computer Science and Technology.

Jun. 2024 – Dec. 2024, New Jersey Institute of Technology

Visiting Ph.D. Student in the Department of Electrical and Computer Engineering

Sep. 2016 – Jul. 2020, China University of Mining and Technology

B.Eng. in Electronic Information Science and Technology, College of Computer Science and Technology (Rank: 5/134).

🎖 Honors and Awards

Dec. 2024, Outstanding graduate student scholarship at Tongji University (BYD scholarship).
Jun. 2020, Outstanding graduate of China University of Mining and Technology.
Nov. 2019, 2018, 2017, First-class scholarship at China University of Mining and Technology

💬 Presentations

Dec. 19, 2024, 2024 IEEE International Workshop on Semiconductor Manufacturing Automation and Robotics,

Trustworthy Multi-Agent Reinforcement Learning under Adversarial Perturbations.

💻 Services