| 2025 | ICML | Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning. | Zhiyao Zhang, Myeung Suk Oh, Hairi, Ziyue Luo, Alvaro Velasquez, Jia Liu |
| 2025 | MOBIHOC | Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization. | Myeung Suk Oh, Zhiyao Zhang, Hairi, Alvaro Velasquez, Jia Liu |
| 2024 | CCS | Byzantine-Robust Decentralized Federated Learning. | Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Gong |
| 2024 | ICML | Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning. | Tianchen Zhou, Hairi, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, Yan Gao |
| 2024 | WiOpt | On the Hardness of Decentralized Multi-Agent Policy Evaluation Under Byzantine Attacks. | Hairi, Minghong Fang, Zifan Zhang, Alvaro Velasquez, Jia Liu |
| 2022 | ICLR | Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward. | Hairi, Jia Liu, Songtao Lu |
| 2021 | MOBIHOC | Beyond Scaling: Calculable Error Bounds of the Power-of-Two-Choices Mean-Field Model in Heavy-Traffic. | Hairi, Xin Liu, Lei Ying |