| 2025 | AAAI | CUQDS: Conformal Uncertainty Quantification Under Distribution Shift for Trajectory Prediction. | Huiqun Huang, Sihong He, Fei Miao |
| 2025 | CIKM | Few-Shot Knowledge Graph Completion via Transfer Knowledge from Similar Tasks. | Lihui Liu, Zihao Wang, Dawei Zhou, Ruijie Wang, Yuchen Yan, Bo Xiong, Sihong He, Hanghang Tong |
| 2025 | ICML | Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning. | Chi Zhang, Ziying Jia, George K. Atia, Sihong He, Yue Wang |
| 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 | ICLR | Robustness Evaluation of Multi-Agent Reinforcement Learning Algorithms using GNAs. | Xusheng Zhang, Wei Zhang, Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He |
| 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 | ICRA | Uncertainty Quantification of Collaborative Detection for Self-Driving. | Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao |
| 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 |