教育经历
威斯康星大学麦迪逊分校，交通工程，博士(2020.06–2023.05)
威斯康星大学麦迪逊分校，计算机科学，硕士(2020.06–2022.05)
威斯康星大学麦迪逊分校，交通工程，硕士(2019.01–2020.05)
天津大学，动力机械及工程，硕士(2017.09–2020.06)
天津大学，计算机科学与技术，学士(2013.09–2017.06)
天津大学，能源与动力工程，学士(2013.09–2017.06)
工作经历
澳门官方十大信誉网站，长聘副教授(2025.04–至今)
威斯康星大学麦迪逊分校，博士后研究员(2023.06–2025.03)
主要研究方向
智能网联汽车、交通流建模与控制优化、AI赋能智能交通系统、人机智能交互等
获奖情况
2024，国家自然基金委优秀青年基金（海外）
2023，上海市白玉兰人才计划（海外）
2023，第一届Onsite自动驾驶算法挑战赛-高速路赛第三名（作为指导教师带队）
2023，威斯康辛研究资助竞赛奖
2022，威斯康辛智能交通协会奖
2021，IEEE“塑造智能交通未来”一等奖
2017，天津大学优秀毕业生
代表性论著
1.Shi, H., Chen, D., Zheng, N., Wang, X., Zhou, Y*., & Ran, B. (2023). A deep reinforcement learning based distributed control strategy for connected automated vehicles in mixed traffic platoon.Transportation Research Part C: Emerging Technologies, 148, 104019. (SCI, JIF: 7.6, Q1)
2.Shi, H., Zhou, Y*., Wang, X., Fu, S., Gong, S., & Ran, B. (2022). A deep reinforcement learning-based distributed connected automated vehicle control under communication failure.Computer-Aided Civil and Infrastructure Engineering, 37(15), 2033–2051. (SCI, JIF: 8.5, Q1)
3.Shi, H., Zhou, Y*., Wu, K., Wang, X., Lin, Y., & Ran, B. (2021). Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment.Transportation Research Part C: Emerging Technologies, 133, 103421. (SCI, JIF: 7.6, Q1)
4.Shi, H., Nie, Q., Fu, S., Wang, X., Zhou, Y*., & Ran, B. (2021). A distributed deep reinforcement learning–based integrated dynamic bus control system in a connected environment.Computer-Aided Civil and Infrastructure Engineering, 36(9), 1147–1164. (SCI, JIF: 8.5, Q1)
5.Shi, H., Zhou, Y., Wu, K., Chen, S., Ran, B., & Nie, Q. (2023).Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles.Knowledge-Based Systems, 110485. (SCI, JIF: 7.2, Q1)
6.Shi, H., Dong, S., Wu, Y., Nie, Q., Zhou, Y., & Ran, B. (2024).Generative adversarial network for car following trajectory generation and anomaly detection.Journal of Intelligent Transportation Systems, 28(1), 1–14. (SCI, JIF: 2.8, Q2)
7.Wu, K., Zhou, Y.,Shi, H*., Li, X., & Ran, B. (2023).Graph-Based Interaction-Aware Multimodal Vehicle Trajectory Prediction.IEEE Transactions on Intelligent Vehicles, 9(2), 3630–3643. (SCI, JIF: 14.0, Q1)
8.Nie, Q., Ou, J., Zhang, H., Li, S., Lu, K., &Shi, H*.(2024). A Robust Integrated Multi-Strategy Bus Control System via Deep Reinforcement Learning.Engineering Applications of Artificial Intelligence, 133, 107986. (SCI, JIF: 7.5, Q1)
9.Long, K.,Shi, H*., Chen, Z., Liang, Z., Li, X*., & de Souza, F. (2023).Bi-scale Car-following Model Calibration for Corridor Based on Trajectory.Transportation Research Part E: Logistics and Transportation Review, 186, 103497. (SCI, JIF: 8.3, Q1)
10.Liu, H.,Shi, H*., Yuan, T., Fu, S., & Ran, B. (2024). Bus Travel Feature Inference with Small Samples Based on Multi-clustering Topic Model over Internet of Things.Future Generation Computer Systems, 163, 107525. (SCI, JIF: 6.2, Q1)
11.Long, K., Sheng, Z.,Shi, H*., Li, X*., Chen, S., & Ahn, S. (2025). Physical enhanced residual learning (PERL) framework for vehicle trajectory prediction.Communications in Transportation Research, 5, 100166. (SCI, JIF: 12.5, Q1)
12.Ma, K.,Shi, H*., Li, X., Ma, C., & Huang, Z*.(2025). Development, Calibration, and Validation of a Novel Nonlinear Car-Following Model: Multivariate Piecewise Linear Approach for Adaptive Cruise Control Vehicles.Transportation Research Part E: Logistics and Transportation Review, 186, 103498. (SCI, JIF: 8.3, Q1)
13.Di, Y., Zhang, W., Ding, H*., Zheng, X., &Shi, H*. (2025). The expressway network design problem for multiple urban subregions based on macroscopic fundamental diagram.Computer-Aided Civil and Infrastructure Engineering, 40(2), 123–140. (SCI, JIF: 8.5, Q1)
14.Shi, H‡., Shi, K‡., Yue, X., Li, W., Zhou, Y*., & Ran, B. (2025). A Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition.IEEE Internet of Things Journal, 12(3), 4567–4578. (SCI, JIF: 8.2, Q1)
15.Tian, K‡.,Shi, H‡., Zhou, Y., & Ran, B. (2025). Physically Analyzable AI based Nonlinear Traffic Dynamics Modeling During Traffic Oscillation: A Koopman Approach.IEEE Transactions on Intelligent Transportation Systems, 26(4), 7890–7902. (SCI, JIF: 7.9, Q1)