| 2025 | AAAI | CUQDS: Conformal Uncertainty Quantification Under Distribution Shift for Trajectory Prediction. | Huiqun Huang, Sihong He, Fei Miao |
| 2025 | IROS | Multi-Agent Reinforcement Learning Guided by Signal Temporal Logic Specifications. | Jiangwei Wang, Shuo Yang, Ziyan An, Songyang Han, Zhili Zhang, Rahul Mangharam, Meiyi Ma, Fei Miao |
| 2025 | IROS | YOLO-MARL: You Only LLM Once for Multi-Agent Reinforcement Learning. | Yuan Zhuang, Yi Shen, Zhili Zhang, Yuxiao Chen, Fei Miao |
| 2025 | ICRA | Safety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles. | Zhili Zhang, H. M. Sabbir Ahmad, Ehsan Sabouni, Yanchao Sun, Furong Huang, Wenchao Li, Fei Miao |
| 2024 | ECCV | MetaAT: Active Testing for Label-Efficient Evaluation of Dense Recognition Tasks. | Sanbao Su, Xin Li, Thang Long Doan, Sima Behpour, Wenbin He, Liang Gou, Fei Miao, Liu Ren |
| 2024 | ICML | Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments. | Han Wang, Sihong He, Zhili Zhang, Fei Miao, James Anderson |
| 2024 | ICML | Constrained Reinforcement Learning Under Model Mismatch. | Zhongchang Sun, Sihong He, Fei Miao, Shaofeng Zou |
| 2023 | IROS | A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems. | Sihong He, Yue Wang, Shuo Han, Shaofeng Zou, Fei Miao |
| 2023 | IROS | Robust Electric Vehicle Balancing of Autonomous Mobility-on-Demand System: A Multi-Agent Reinforcement Learning Approach. | Sihong He, Shuo Han, Fei Miao |
| 2023 | IROS | Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles. | Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su |
| 2023 | ICRA | Uncertainty Quantification of Collaborative Detection for Self-Driving. | Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao |
| 2023 | ICRA | Spatial-Temporal-Aware Safe Multi-Agent Reinforcement Learning of Connected Autonomous Vehicles in Challenging Scenarios. | Zhili Zhang, Songyang Han, Jiangwei Wang, Fei Miao |
| 2022 | ICRA | Stable and Efficient Shapley Value-Based Reward Reallocation for Multi-Agent Reinforcement Learning of Autonomous Vehicles. | Songyang Han, He Wang, Sanbao Su, Yuanyuan Shi, Fei Miao |
| 2021 | EMNLP | A Secure and Efficient Federated Learning Framework for NLP. | Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding |
| 2021 | ICDE | Data-Driven Fairness-Aware Vehicle Displacement for Large-Scale Electric Taxi Fleets. | Guang Wang, Shuxin Zhong, Shuai Wang, Fei Miao, Zheng Dong, Desheng Zhang |
| 2021 | IJCAI | Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. | Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao |
| 2021 | IROS | Automated Type-Aware Traffic Speed Prediction based on Sparse Intelligent Camera System. | Xiaoyang Xie, Kangjia Shao, Yang Wang, Fei Miao, Desheng Zhang |
| 2020 | IROS | Data-Driven Distributionally Robust Electric Vehicle Balancing for Mobility-on-Demand Systems under Demand and Supply Uncertainties. | Sihong He, Lynn Pepin, Guang Wang, Desheng Zhang, Fei Miao |
| 2019 | ICDCS | p^2Charging: Proactive Partial Charging for Electric Taxi Systems. | Yukun Yuan, Desheng Zhang, Fei Miao, Jimin Chen, Tian He, Shan Lin |
| 2017 | IROS | Artificial invariant subspace with potential functions for humanoid robot balancing. | Xiang Deng, Fei Miao, Daniel D. Lee |