Educational background

Ph.D.in Transportation Engineering, University of Wisconsin–Madison, USA (Jun. 2020 – May 2023)

M.S.in Computer Sciences, University of Wisconsin–Madison, USA (Jun. 2020 – May 2022)

M.S. in Transportation Engineering, University of Wisconsin–Madison, USA (Jan. 2019 – May 2020)

M.S. in Power Machinery and Engineering, Tianjin University, China (Sep. 2017 – Jun. 2020)

B.S.in Computer Science and Technology, Tianjin University, China (Sep. 2013 – Jun. 2017)

B.S.in Energy and Power Engineering, Tianjin University, China (Sep. 2013 – Jun. 2017)

Work experience

Tenured Associate Professor, Tongji University, China (Apr. 2025 – Present)

Postdoctoral Research Associate, University of Wisconsin–Madison, USA (Jun. 2023 – Mar. 2025)

Research interests

Autonomous driving behavior modeling and control optimization;End-to-end algorithm testing and scenario generation;Intelligent driver–vehicle interaction,Intelligent connected transportation system

Honors & Awards

·2025, Shanghai “Morning Light Program” Scholar

·2024, National Science Fund for Outstanding Young Scholars (Overseas), NSFC

·2023, Shanghai Magnolia Talent Program (Overseas)

·2023, 3rd Place, Highway Track, 1st Onsite Autonomous Driving Algorithm Challenge (as faculty advisor)

·2023, Wisconsin Research Funding Competition Award

·2022, Wisconsin Intelligent Transportation Society Award

·2021, First Prize, IEEE “Shaping the Future of Intelligent Transportation” Competition

·2017, Outstanding Graduate, Tianjin University

Selected Publications (*Corresponding Author):

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.Li, Z., Bao, Z., Meng, H.,Shi, H*., Li, Q*., Yao, H., & Li, X. (2025). Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs.Communications in Transportation Research(SCI, JIF: 14.5, Q1)

16.You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z.,Shi, H*et al. (2024). FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction. Accepted byCommunications in Transportation Research(SCI, JIF: 14.5, Q1)

17.Di, Y., Zhang, W., Ding, H*.,Shi, H*., You, J., Li, H., & Ran, B. (2025). A Cooperation Control for Multiple Urban Regions Traffic Flow Coupled With an Expressway Network.IEEE Transactions on Network Science and Engineering. (SCI, JIF: 7.9, Q1)

18. Gan, R.,Shi, H*., Li, P*., Wu, K., An, B., Li, L., ... & Ran, B. (2025). Goal-based Neural Physics Vehicle Trajectory Prediction Model.Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)

19.Wu, K., Zhou, Y*., Shi, H*., Lord, D., Ran, B., & Ye, X. (2025). Hypergraph-based motion generation with multi-modal interaction relational reasoning.Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)

20.You, J.,Shi, H*., Jiang, Z., Huang, Z., Gan, R., Wu, K., ... & Ran, B. (2026).V2x-vlm: End-to-end v2x cooperative autonomous driving through large vision-language models. Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)