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石皓天 长聘副教授、研究员、博导

石皓天 长聘副教授、研究员、博导

性别 男 出生年月 1995-01
最终学历 博士 职称 长聘副教授、研究员、博导
E-mail shihaotian95@tongji.edu.cn

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个人简介

石皓天（Haotian Shi），男，1995年生，籍贯重庆，同济大学交通学院研究员/长聘副教授，国自然优秀青年科学基金（海外）获得者（2024）。博士毕业于美国威斯康星大学麦迪逊分校，拥有交通工程（博士+硕士）、计算机科学（硕士+学士）、动力机械及工程（硕士+学士）多学位教育背景。

主要研究方向包括自动驾驶行为建模与控制优化、端到端算法测试与场景生成、智能驾驶人机交互、智能网联交通系统等。主持国家自然科学基金3项（优青（海外）、面上项目、青年C类）等多项国家级、省部级项目。已发表学术论文80余篇，其中以一作/通讯在TR Part C/E、IEEE T-ITS、CACAIE、COMMTR等中科院一区TOP SCI发表近30篇。授权中美发明专利30余项。在ECCV、INFORMS、IEEE IV/ITSC、TRB等国际学术会议作学术报告50余次。入选国家级青年人才计划、上海市白玉兰人才计划（海外）、上海市晨光计划。获国家自然科学基金委指导的首届OnSite自动驾驶算法挑战赛高速赛段第三名（指导教师带队）、美国威斯康辛智能交通协会奖、SAE汽车智能交通技术创新奖一等奖、IEEE“塑造智能交通未来”一等奖等奖项。担任《GEITS》等一区期刊编委/青年编委，AAAI、ITFT等国际会议程序委员会委员，世界交通运输大会（WTC）智能云管云控、智能网联与车路协同控制、CAV政策法规、智能驾驶出行服务等技术委员会国际委员，中国公路学会高级会员。


研究方向

自动驾驶行为建模与控制优化、端到端算法测试与场景生成、智能驾驶人机交互、智能网联交通系统等


教育经历

·2020.06–2023.05：威斯康星大学麦迪逊分校，交通工程，博士（导师：冉斌教授）

·2020.06–2022.05：威斯康星大学麦迪逊分校，计算机科学，硕士

·2019.01–2020.05：威斯康星大学麦迪逊分校，交通工程，硕士

·2017.09–2020.06：天津大学，动力机械及工程，硕士（导师：赵华教授、谢辉教授）

·2013.09–2017.06：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


工作经历

·2025.04–至今：同济大学，研究员/长聘副教授（青年百人A岗）

·2023.06–2025.03：威斯康星大学麦迪逊分校，博士后研究员（合作导师：李小鹏教授）


办公室

同济大学嘉定校区通达馆A503


研究成果

期刊论文（*表示通讯作者）

  1. Cui, Y., Fang, S., Zhang, G., Shi, H., Hang, P., Zhang, H., & Sun, J. (2027). V2I-LENC: A vehicle-infrastructure language-enhanced negotiation and cooperation chain for mixed-traffic. Transportation Research Part C: Emerging Technologies, 194, 105979.

  2. Wang, J., Shi, H., Zhao, Y., Zhao, X., Liang, H., Hang, P., & Sun, J. (2027). Chain-like cognitive processes in human-machine co-driving: Uncovering causal-chain mechanisms of driver takeover failure. Transportation Research Part C: Emerging Technologies, 194, 105972.

  3. Wang, J., Zhao, Y., Zhao, X., Shi, H.*, & Sun, J. (2026). Toward driver stage-wise takeover behavior in autonomous driving: A cognitive process modeling approach for adaptive takeover requests design. Transportation Research Part C: Emerging Technologies, 105930. (SCI, Q1)

  4. You, J., Li, P., Jiang, Z., Huang, Z., Gan, R., Shi, H., & Ran, B. (2026). SEAL: Vision-language model-based safe end-to-end cooperative autonomous driving with adaptive long-tail modeling. Accident Analysis & Prevention, 238, 108748.

  5. Fu, S., Shi, H.*, Liang, S., Ma, W., & Ran, B. (2026). Recovering large-scale urban traffic flow data from sparse observations via analytical optimization. Computer-Aided Civil and Infrastructure Engineering, 51, 100180. (SCI, Q1)

  6. Chen, Q., Liu, X., Ding, S., Chen, S., Shi, H., & Liang, J. (2026). Observer-based control for vehicle platoons under uncertainties and measurement noise. Journal of the Franklin Institute, 363(15), 109016.

  7. Long, K., Shi, H., Liang, S., & Li, X. (2026). Physics enhanced residual policy learning (PERPL) for safety cruising in mixed traffic platooning under actuator and communication delay. Transportation Research Part C: Emerging Technologies, 190, 105792.

  8. Liang, S., Ma, C., Li, P., Shi, H., Liu, J., Zhou, H., Long, K., Cao, B., Szymkowski, T., Shi, X., & Li, X. (2026). Real-time lane-level abnormal traffic detection on freeways using sparse telematics data. Accident Analysis & Prevention, 234, 108607.

  9. Mao, J., Liu, L., Huang, H., Lu, W., Yang, K., Tang, T., & Shi, H.*. (2026). Estimating urban traffic patterns through GPS trace data from car-hailing vehicles: A temporal-spatial analysis. Journal of Transportation Engineering, Part A: Systems, 152(9).

  10. Di, Y., Zhang, W., Ding, H.*, Shi, H.*, Zheng, X., & Ran, B. (2026). Cooperative route guidance and flow control for mixed networks comprising expressway and arterial network. IEEE Transactions on Automation Science and Engineering, 23, 13136–13153. (SCI, JIF: 7.9, Q1)

  11. 孙剑，王洁，蒋溪彦，石皓天，李子睿，赵晓聪. (2026). 自动驾驶汽车驾驶人分阶段接管反应时间预测[J/OL]. 中国公路学报, 1–25 [2026-06-07]. https://link.cnki.net/urlid/61.1313.u.20260507.1320.002.

  12. Wang, J., Dong, J., Shi, H.*, Sundaram, S., Labi, S., & Chen, S.* (2026). Reinforcement learning based mobile energy disseminator dispatching for on-road electric vehicle charging. Multimodal Transportation, 5(1), 100232. (SCI, JIF: 8, Q1)

  13. Long, K., Shi, H., Liu, J., Xiao, C., & Li, X. (2026). VLM-MPC: Model predictive controller augmented vision language model for autonomous driving. Transportation Research Part C: Emerging Technologies, 183, 105487.

  14. You, J., Jiang, Z., Huang, Z., Shi, H.*, Gan, R., Wu, K., Cheng, X., Li, X., & Ran, B. (2026). V2X-VLM: End-to-end V2X cooperative autonomous driving through large vision-language models. Transportation Research Part C: Emerging Technologies, 183, 105457. (SCI, JIF: 7.9, Q1)

  15. You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z., Shi, H.*, et al. (2025). FollowGen: A scaled noise conditional diffusion model for car-following trajectory prediction. Communications in Transportation Research, 5, 100215. (SCI, JIF: 14.5, Q1)

  16. 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, 180, 105349. (SCI, JIF: 7.9, 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, 12(6), 5058–5072. (SCI, JIF: 7.9, Q1)

  18. Gan, R., Shi, H.*, Li, P.*, Wu, K., An, B., You, J., Li, L., Ma, J., Ma, C., & Ran, B. (2025). Goal-based neural physics vehicle trajectory prediction model. Transportation Research Part C: Emerging Technologies, 179, 105283. (SCI, JIF: 7.9, Q1)

  19. Zhang, P., Huang, H., Zhou, H., Shi, H., Long, K., & Li, X. (2025). Online adaptive platoon control for connected and automated vehicles via physics enhanced residual learning. Transportation Research Part C: Emerging Technologies, 178, 105242.

  20. 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, 5, 100201. (SCI, JIF: 14.5, Q1)

  21. Ma, C., Zhou, H., Zhang, P., Ma, K., Shi, H., & Li, X. (2025). Safety assurance adaptive control for modular autonomous vehicles. Communications in Transportation Research, 5, 100204.

  22. Shi, H.‡, Shi, K.‡, Wu, K., 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(14), 26943–26954. (SCI, JIF: 8.2, Q1)

  23. Tian, K.‡, Shi, H.‡, Zhou, Y., & Li, S. (2025). Physically analyzable AI-based nonlinear platoon dynamics modeling during traffic oscillation: A Koopman approach. IEEE Transactions on Intelligent Transportation Systems, 26(7), 10105–10115. (SCI, JIF: 7.9, Q1)

  24. Ma, K., Shi, H.*, Ma, C., Huang, Z., Wang, Q., & Li, X. (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, 199, 104031. (SCI, JIF: 8.3, Q1)

  25. Di, Y., Zhang, W., Shi, H.*, Ding, H.*, Huo, J., & Ran, B. (2025). The expressway network design problem for multiple urban subregions based on the macroscopic fundamental diagram. Computer-Aided Civil and Infrastructure Engineering, 40(14), 2032–2049. (SCI, JIF: 8.5, Q1)

  26. 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)

  27. Long, K., Ma, C., Li, H., Li, Z., Huang, H., Shi, H., Huang, Z., Sheng, Z., Shi, L., Li, P., Chen, S., & Li, X. (2025). AI-enabled digital twin framework for safe and sustainable intelligent transportation. Sustainability, 17(10), 4391. (SCI, JIF: 3.3, Q2)

  28. Liu, H., Shi, H.*, Yuan, T., Fu, S., & Ran, B. (2025). 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)

  29. Shi, H., Dong, S., Wu, Y., Nie, Q., Zhou, Y., & Ran, B. (2025). Generative adversarial network for car following trajectory generation and anomaly detection. Journal of Intelligent Transportation Systems, 29(1), 53–66. (SCI, JIF: 2.8, Q2)

  30. Long, K., Liang, Z., Shi, H., Shi, L., Chen, S., & Li, X. (2024). Traffic oscillation mitigation with physics-enhanced residual learning (PERL)-based predictive control. Communications in Transportation Research, 4, 100154. (SCI, JIF: 12.5, Q1)

  31. Yue, X., Shi, H., Zhou, Y., & Li, Z. (2024). Hybrid car following control for CAVs: Integrating linear feedback and deep reinforcement learning to stabilize mixed traffic. Transportation Research Part C: Emerging Technologies, 167, 104773. (SCI, JIF: 7.6, Q1)

  32. Nie, Q., Ou, J., Zhang, H., Lu, J., Li, S., & 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)

  33. Long, K., Shi, H.*, Chen, Z., Liang, Z., Li, X.*, & de Souza, F. (2024). Bi-scale car-following model calibration based on corridor-level trajectory. Transportation Research Part E: Logistics and Transportation Review, 186, 103497. (SCI, JIF: 8.3, Q1)

  34. Wu, R., Li, L., Shi, H., Rui, Y., Ngoduy, D., & Ran, B. (2024). Integrated driving risk surrogate model and car-following behavior for freeway risk assessment. Accident Analysis & Prevention, 201, 107571. (SCI, JIF: 5.7, Q1)

  35. Wu, K., Zhou, Y., Shi, H.*, Li, X., & Ran, B. (2024). Graph-based interaction-aware multimodal 2D vehicle trajectory prediction using diffusion graph convolutional networks. IEEE Transactions on Intelligent Vehicles, 9(2), 3630–3643. (SCI, JIF: 14.0, Q1)

  36. Liu, C., Sheng, Z., Chen, S., Shi, H., & Ran, B. (2023). Longitudinal control of connected and automated vehicles among signalized intersections in mixed traffic flow with deep reinforcement learning approach. Physica A: Statistical Mechanics and its Applications, 629, 129189. (SCI, JIF: 2.8, Q2)

  37. Liu, H., Wu, K., Fu, S., Shi, H.*, & Xu, H. (2023). Predictive analysis of vehicular lane changes: An integrated LSTM approach. Applied Sciences, 13(18), 10157. (SCI, JIF: 2.8, Q2)

  38. 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, 269, 110485. (SCI, JIF: 7.2, Q1)

  39. 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, Top Cited in Part C)

  40. 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)

  41. Shi, H., Nie, Q., Fu, S., Wang, X., Zhou, Y.*, & Ran, B. (2022). A distributed deep reinforcement learning-based integrated dynamic bus control system in a connected environment. Computer-Aided Civil and Infrastructure Engineering, 37(15), 2016–2032. (SCI, JIF: 8.5, Q1)

  42. Shi, K., Wu, Y., Shi, H., Zhou, Y., & Ran, B. (2022). An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network. Physica A: Statistical Mechanics and its Applications, 599, 127303. (SCI, JIF: 2.8, Q2)

  43. 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)

  44. Wu, Z., Chen, T., Xie, H., Shi, H., Yang, Z., & Zhao, H. (2019). Optimization of valve strategy for high compression-ratio gasoline engine operating with Miller cycle. Journal of Combustion Science and Technology, 25(4), 331–339. (EI, JIF: 1.7, Q3)

  45. Dong, H., Shi, H., Wang, G., & Zhao, F. Skillful use of technology to ensure equipment shape and position tolerance requirements. Journal of Ordnance Equipment Engineering, 33(12), 49–50. (中文核心期刊)


客座讲座:

  1. Course CVEN 307 Transportation System at Texas A&M University. “Topic: A deep reinforcement learning-based distributed connected automated vehicle control under communication failure” (2022).

  2. Course CVEN 456 Urban Traffic Facilitiesat Texas A&M University. “Topic: A deep reinforcement learning based distributed control strategy for connected automated vehicles in mixed traffic platoon” (2023).


会议论文及受邀报告

  1. Ding, S., Luo, X., Wang, J., & Shi, H.* (2027). Macroscopic–Microscopic Cooperative Control for Disturbance Suppression in Mixed Traffic Flow under Non-Recurrent Traffic Incidents. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  2. Cao, Y., Li, S., Zhao, Y., Wang, C., Zhou, H., & Shi, H.* (2027). Scene2Flow: Evaluating End-to-End Autonomous Driving Beyond the Ego Vehicle. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  3. Wang, J., Zhao, Y., Sun, J., & Shi, H.* (2027). Recovering Driver Attention to High-Risk Traffic Actors During Automated-Driving Takeovers Under Ocular Degradation. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  4. Sun, B., Li, Q., Ni, Y., & Shi, H.* (2027). Clustering and Characterization of Heterogeneous Pedestrian Crossing Behavior in Explicit–Implicit Interaction with AVs: A Measure–Analysis–Pattern Framework. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  5. Wang, Y., & Shi, H.* (2027). SIFNet: Selective Interaction Forecasting Network for Vehicle Motion Prediction in Highly Interactive Urban Driving Scenarios. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  6. Li, S., Zhao, Y., Cao, Y., Ni, Y., & Shi, H.* (2027). EchoSplat: Self-Improving Camera-LiDAR Neural Simulation for Autonomous Driving Testing. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  7. Xu, J., Xu, C., Peng, B., Zhao, Y., & Shi, H.* (2027). LLM-MAC: Large Language Model-Orchestrated Multi-Agent Control for Non-Recurrent Traffic Management. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  8. Xie, A., Zhao, Y., & Shi, H.* (2027). RiskStage-3D: Scalable Generation of 3D Safety-Critical Scenarios for End-to-End Autonomous Driving Models via Semantic Feed-Forward Gaussian Splatting. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  9. Li, Q., Tang, T., Sun, B., & Shi, H.* (2027). Traffic-Regulation-Grounded Motion Planning with Vision-Language Models for Autonomous Driving. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  10. Xie, A., & Shi, H.* (2027). RiskMatrix-3D: Dual-Risk Controllable Closed-Loop Testing for End-to-End Autonomous Driving Based on 3D Gaussian Splatting. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  11. Zhao, Y., Wang, J., Li, S., Cao, Y., Ni, Y., & Shi, H. (2027). Allocating Offline Driving Logs for Closed-Loop Automated-Driving Performance: Sparse Target Feedback across Scenario Families. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  12. Zhao, Y., Wang, J., Xu, J., Ni, Y., & Shi, H. (2027). Evaluating the Trustworthiness of Vision–Language Reasoning for Vulnerable Road User Interactions: A Difficulty-Stratified Study. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  13. Zhao, Y., Wang, J., Li, Y., Xie, A., Ni, Y., & Shi, H. (2027). Reallocating Closed-Loop Training Exposure for Pre-Crash Safety: Risk Staging and Corrective Replay. 106th Annual Meeting of the Transportation Research Board (TRB 2027), Washington, D.C.

  14. He et al. (2026). A Multi-Strategy Cooperative Control Decision Generation Framework for Non-Recurrent Traffic. CAA International Conference on Vehicular Control and Intelligence (CVCI 2026).

  15. Shi, H. (2026). OnSite Autonomous Driving Public Testing Service Platform. The 7th Workshop on Intelligent Transportation Systems between Tongji University and the University of Tokyo 2026.

  16. Huang, R., Bai, Y., & Shi, H.* (2026). Graph Model-Driven Causal Inference for Non-Motorized Vehicle Behavior. IEEE Intelligent Transportation Systems Conference (ITSC 2026).

  17. Li, S., Ni, Y.*, Sun, J., Sun, J., & Shi, H.* (2026). DecoupleGS: Interactive 3D Gaussian Splatting for End-to-End Autonomous Driving Testing. European Conference on Computer Vision (ECCV 2026, Main Conference).

  18. Shi, H. (2026). 自动驾驶人机共融：驾驶人认知感知与智能交互. 医学人工智能研究院（脑机脑智领域）专题研讨会，2026年9月.

  19. Shi, H. (2026). AI-Empowered Autonomous Driving: Behavior Modeling, Control Optimization, and End-to-End Testing. The 26th COTA International Conference of Transportation Professionals (CICTP 2026), Young Scholars Forum. (Invited Oral Presentation)

  20. You, J., Shi, H.*, et al. (2026). FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction. The 15th Asia-Pacific Conference on Transportation and the Environment (APTE 2026).

  21. Wang, J., Zhao, Y., Shi, H.*, & Sun, J. (2026). Optimizing Takeover Request Strategies in Automated Driving: A Behavioral Stage-Based Cognitive Process Modeling Approach. IEEE Intelligent Vehicles Symposium (IV 2026). (Oral Presentation, 8% of accepted papers)

  22. Shi, H. (2026). 端到端协同自动驾驶方法与虚实融合测试平台. 同济大学青讲论坛，2026年5月.

  23. Shi, H. (2026). End-to-End V2X Cooperative Autonomous Driving Method for Safety and Long-Tail Generalization. 2026 China Intelligent New Energy Vehicles and Smart Transportation Young Scholars Forum (AUTO-E 2026). (Invited Oral Presentation)

  24. Nie, T., Mei, Y., Tang, Y., He, J., Sun, J., Shi, H., ... & Sun, J. (2026). Steerable Adversarial Scenario Generation through Test-Time Preference Alignment. International Conference on Learning Representations (ICLR 2026).

  25. Bai, Y., Huang, R., & Shi, H.* (2026). DyScene Enhancing Physical Realism: A Physics-Informed Graph Convolutional Network for Multimodal Stochastic Bicycle Trajectories Prediction. 105th Annual Meeting of the Transportation Research Board (TRB 2026), Washington, D.C.

  26. Liang, S., Ma, C., Li, P., Shi, H., Liu, J., & Li, X. (2026). Real-Time Lane-Level Crash Detection on Freeways Using Sparse Telematics Data. 105th Annual Meeting of the Transportation Research Board (TRB 2026), Washington, D.C.

  27. Xie, C., Zheng, Y., Li, S., Bai, L., Shi, H., & Ran, B. (2025). A Physics-Informed Neural Network for Lane-Changing Trajectory Reconstruction from Noisy and Sparse Observations. The 29th International Conference of the Hong Kong Society for Transportation Studies (HKSTS 2025).

  28. Shi, H. (2025). Construction Technology of Virtual–Real Fusion Testing Platform for Autonomous Driving. RISE Week 2025: Co-Creating Resilient Urban Futures. (Presentation)

  29. Ma, C., Zhou, H., Zhang, P., Ma, K., Shi, H., & Li, X. (2025). Safety Assurance Adaptive Control in Automated Vehicles: A Case Study on Modular Vehicles. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  30. Zhang, P., Zhou, H., Huang, H., Shi, H., Long, K., & Li, X. (2025). Online Adaptive Platoon Control for Connected and Automated Vehicles via Physical Enhanced Residual Learning. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  31. You, J., Shi, H.*, Wu, K., Long, K., Fu, S., Chen, S.*, & Ran, B. (2025). Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  32. Ma, K., Zhou, H., Zhang, Y., Shi, H., Ma, C., Li, Z., Zhang, P., Liang, Z., & Li, X. (2025). Automated Vehicle Longitudinal Stability Analysis: Controller Design and Field Test. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  33. Long, K., Shi, H., Zhou, Y., & Li, X. (2025). Physics Enhanced Residual Policy Learning (PERPL) for Safety Cruising in Mixed Traffic Platooning under Actuator and Communication Delay. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  34. Long, K., Shi, H., Liu, J., & Li, X. (2025). VLM-MPC: Vision Language Foundation Model (VLM)-Guided Model Predictive Controller (MPC) for Autonomous Driving. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  35. Ma, K., Zhou, H., Shi, H., Ma, C., & Li, X. (2025). Understanding Autonomous Vehicle Behavior: A Soft-Margin Approach in Piecewise Linear Model. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  36. Gan, R., Shi, H.*, Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., & Ran, B. (2025). Goal-Based Neural Physics Vehicle Trajectory Prediction Model. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  37. You, J., Shi, H.*, Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li, X., & Ran, B. (2025). V2X-VLM: End-to-End V2X Cooperative Autonomous Driving through Large Vision-Language Models. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  38. Huo, J., Liang, Z., Shi, H.*, Ma, K., Li, X., & Liu, Z. (2025). Vehicle Trajectory Tracking on Snowy Roads: A Model Predictive Control Method. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  39. Wu, K., Shi, H.*, Zhou, Y.*, & Ran, B. (2025). Hypergraph-Based Motion Generation and Planning with Multi-Modal Interaction Relational Reasoning. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  40. Long, K., Liang, Z., Shi, H., Shi, L., Chen, S., & Li, X. (2025). Traffic Oscillations Mitigation with Physics Enhanced Residual Learning (PERL)-Based Predictive Control. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  41. 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. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  42. Tian, K.#, Shi, H.#, Zhou, Y., & Li, S. (2025). Physically Analyzable AI-Based Nonlinear Platoon Dynamics Modeling During Traffic Oscillation: A Koopman Approach. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  43. Di, Y., Shi, H.*, Zhang, W., Ding, H., Zheng, X., & Ran, B. (2025). Cooperative Route Guidance and Flow Control for Mixed Road Networks Comprising Expressway and Arterial Network. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  44. Di, Y., Zhang, W., Shi, H.*, Ding, H., Huo, J., & Ran, B. (2025). The Expressway Network Design Problem for Multiple Urban Subregions Based on the Macroscopic Fundamental Diagram. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  45. Di, Y., Zhang, W., You, J., Shi, H.*, Li, H., Ding, H., & Ran, B. (2025). A Cooperative Flow Control for Multiple Urban Regions Coupled with an Expressway Network. 104th Annual Meeting of the Transportation Research Board (TRB 2025), Washington, D.C.

  46. Long, K., Shi, H.*, Sheng, Z., Li, X.*, & Chen, S. (2024). ASCE International Conference on Transportation and Development (ICTD 2024).

  47. Zhou, H., Huang, H.*, Zhang, P., Li, X.*, Shi, H., & Long, K. (2024). Online Physical Enhanced Residual Learning for Connected Autonomous Vehicles Platoon Centralized Control. IEEE Intelligent Vehicles Symposium (IV 2024). arXiv preprint arXiv:2402.11468.

  48. Shi, H., Dong, S., Wu, Y., Li, S., Zhou, Y., & Ran, B. (2024). Generative Adversarial Network for Car Following Trajectory Generation and Anomaly Detection. 103rd Annual Meeting of the Transportation Research Board (TRB 2024), Washington, D.C. (Poster)

  49. Wu, K., Zhou, Y., Shi, H.*, Li, X., & Ran, B. (2024). Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional Networks. 103rd Annual Meeting of the Transportation Research Board (TRB 2024), Washington, D.C. (Poster)

  50. Long, K., Sheng, Z., Shi, H.*, Li, X.*, Chen, S., & Ahn, S. (2024). A Physics Enhanced Residual Learning (PERL) Framework for Vehicle Trajectory Prediction. 103rd Annual Meeting of the Transportation Research Board (TRB 2024), Washington, D.C. (Poster)

  51. Long, K., Shi, H.*, Chen, Z., Liang, Z., Li, X.*, & Souza, F. (2024). Bi-Scale Car-Following Model Calibration for Corridor Based on Trajectory. 103rd Annual Meeting of the Transportation Research Board (TRB 2024), Washington, D.C. (Poster)

  52. Ma, K., Li, X., Shi, H., Ma, C., Huang, Z., Ghiasi, A., Wang, Q., Hourdos, J., & McHale, G. (2024). A Novel Non-Linear Car-Following Model for Automated Vehicle: Development, Calibration, and Validation. 103rd Annual Meeting of the Transportation Research Board (TRB 2024), Washington, D.C. (Poster)

  53. Shi, H. (2023). Mixed Platoon Control Strategy of Connected Automated Vehicles Based on Physics-Informed Deep Reinforcement Learning. INFORMS Annual Meeting 2023. (Panel Speaker)

  54. Shi, H. (2023). Mixed Platoon Control Strategy of Connected and Automated Vehicles Based on Physics-Informed Deep Reinforcement Learning. Young Faculty & Practitioner Workshop, ASCE International Conference on Transportation and Development (ICTD 2023). Presentation ID: 2438399. (Panel Speaker)

  55. Chen, T., Shi, H.*, Parker, S. T., Vorhes, G., & Noyce, D. A. (2023). Conceptual Development for a Generalized Tribal Crash Safety Dashboard. ASCE International Conference on Transportation and Development (ICTD 2023). Presentation ID: 2252954. (Poster)

  56. Chen, T., Shi, H.*, Parker, S. T., Vorhes, G., & Noyce, D. A. (2023). Conceptual Development for a Generalized Tribal Crash Safety Dashboard. 102nd Annual Meeting of the Transportation Research Board (TRB 2023), Washington, D.C. TRBAM-23-02333. (Podium)

  57. Shi, H., Chen, D., Zheng, N., Wang, X., Zhou, Y., & Ran, B. (2023). Distributed Connected Automated Vehicles Control under Real-Time Aggregated Macroscopic Car-Following Behavior Estimation Based on Deep Reinforcement Learning. 102nd Annual Meeting of the Transportation Research Board (TRB 2023), Washington, D.C. TRBAM-23-02403. (Poster)

  58. Chen, T., Shi, H.*, Vorhes, G., Parker, S. T., & Noyce, D. A. (2022). How to Collect Tribal Crash Data Properly? Experience from a New Wisconsin Crash Reporting System. ASCE International Conference on Transportation and Development (ICTD 2022), pp. 48–60. (Conference Proceedings)

  59. Chen, T., Shi, H.*, Vorhes, G., Parker, S. T., & Noyce, D. A. (2022). Tribal Crash Reporting System Improvements in Wisconsin. 101st Annual Meeting of the Transportation Research Board (TRB 2022), Washington, D.C. TRBAM-22-02539. (Podium)

  60. Shi, H., Nie, Q., Fu, S., Wang, X., Zhou, Y., & Ran, B. (2022). A Distributed Deep Reinforcement Learning Based Integrated Dynamic Bus Control System in a Connected Environment. 101st Annual Meeting of the Transportation Research Board (TRB 2022), Washington, D.C. TRBAM-22-00882. (Poster)

  61. 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. ASCE T&DI Technical Committee on Artificial Intelligence Student Competition. (Top 10 in Competition)

  62. Chen, T., Shi, H., Vorhes, G., Parker, S. T., & Noyce, D. A. (2020). Data and System Architecture Improvements for Statewide Crash Mapping and Analysis. 99th Annual Meeting of the Transportation Research Board (TRB 2020), Washington, D.C. Paper No. 20-05109. (Poster)


已授权中美发明专利

  1. Ni, Y., Li, S., Shi, H., & Sun, J. (2026). Three-Dimensional Gaussian Scene Simulation Method and System for End-to-End Autonomous Driving Testing. Chinese Patent [CN122473353B].

  2. Ran, B., Chen, T., Dong, S., Cheng, Y., Zhang, M., Li, X., Li, S., Shi, K., Shi, H., Yao, Y., Mo, Y., Liu, H., Wu, K., & Yi, R. (2026). Function Allocation and Integration for Autonomous Vehicles. U.S. Patent [US 12,709,303 B2].

  3. Ran, B., Fu, S., Gan, R., Cheng, Y., Li, S., Tian, K., Chen, T., Dong, S., Shi, K., Shi, H., & Li, X. (2026). Distributed Computing for Autonomous Vehicles. U.S. Patent [US 12,602,998 B2].

  4. Ran, B., An, B., Zhou, Z., Li, M., Wu, K., Cheng, Y., Yao, Y., Shi, H., Chen, T., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2025). Roadside Edge Computing System for Autonomous Vehicles. U.S. Patent [US 12,333,932 B2].

  5. Ran, B., Shi, K., Lu, W., Cheng, Y., Zhang, H., Shi, H., Chen, T., Liang, B., Yao, Y., Wu, K., & Fu, S. (2025). Connected Reference Marker System. U.S. Patent [US 12,333,935 B2].

  6. Ran, B., Wang, Z., Wu, R., Jiang, J., Cheng, Y., Wu, K., Yao, Y., Chen, T., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2025). Vehicle AI Computing System (VACS) for Autonomous Driving. U.S. Patent [US 12,327,471 B2].

  7. Chen, T., Ran, B., Dong, S., Wu, K., Cheng, Y., Li, L., Li, S., Li, X., Mo, Y., Yao, Y., Shi, K., Shi, H., & Li, H. (2025). Systematic Intelligent System. U.S. Patent [US 12,326,731 B2].

  8. Ran, B., Zhao, K., Li, H., Zhang, M., Li, S., Cheng, Y., Chen, Z., Ye, J., Dong, S., & Shi, H. (2025). Vehicle Intelligent Unit. U.S. Patent [US 12,325,434 B2].

  9. Ran, B., Dong, S., Cheng, Y., Chen, T., Li, S., Li, X., Shi, K., Shi, H., Wu, K., Yao, Y., & Yi, R. (2025). Device Allocation System. U.S. Patent [US 12,279,191 B2].

  10. Ran, B., Zheng, Y., Wang, C., Cheng, Y., Yao, Y., Wu, K., Chen, T., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2025). Autonomous Vehicle Cloud System. U.S. Patent [US 12,266,262 B2].

  11. Ran, B., Liang, B., Zhao, Y., Cheng, Y., Yao, Y., Wu, K., Chen, T., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2025). Autonomous Vehicle Intelligent System (AVIS). U.S. Patent [US 12,260,746 B2].

  12. Ran, B., Li, S., Cheng, Y., Chen, T., Dong, S., Shi, K., Shi, H., & Li, X. (2024). Distributed Driving System and Method for an Autonomous Driving Vehicle. Chinese Invention Patent [CN114585876B].

  13. Ran, B., Mao, P., Lu, W., Yi, Z., Li, L., Cheng, Y., Xu, L., Zheng, Y., Chen, T., Shi, H., & Wu, K. (2024). Function Allocation for Automated Driving Systems. U.S. Patent [US 12,077,175 B2].

  14. Ran, B., Cheng, Y., Li, S., Tian, K., Chen, T., Dong, S., Shi, K., Shi, H., & Li, X. (2024). Distributed Driving with Flexible Roadside Resources. U.S. Patent [US 12,046,136 B2].

  15. Ran, B., Chen, T., Dong, S., Cheng, Y., Zhang, M., Li, X., Li, S., Shi, K., Shi, H., Yao, Y., Mo, Y., Liu, H., Wu, K., & Yi, R. (2024). Function Allocation for Automated Driving Systems. U.S. Patent [US 12,037,023 B2].

  16. Ran, B., Cheng, Y., Chen, T., Yao, Y., Wu, K., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2024). Autonomous Vehicle and Cloud Control System. U.S. Patent [US 12,020,563 B2].

  17. Ran, B., Cheng, Y., Chen, T., Yao, Y., Wu, K., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2024). Autonomous Vehicle (AV) Control System with Roadside Unit (RSU) Network. U.S. Patent [US 12,008,893 B2].

  18. Ran, B., Chen, T., Li, S., Cheng, Y., Li, L., Zhou, Z., He, S., Li, X., Dong, S., Yao, Y., Shi, K., Shi, H., Wu, K., & Fu, S. (2023). Collaborative Autonomous Driving System. Chinese Patent Application [CN117087695A].

  19. Nie, Q., Zhang, H., Ou, J., Jing, P., Yue, P., Zhou, Y., Shi, H., & Xiao, X. (2023). Multi-Strategy Fusion Control Method for Bus Operation in an Intelligent Networking Environment. Chinese Invention Patent [CN115691196B].

  20. Ran, B., Zhao, K., Li, H., Zhang, M., Chen, Z., Jiang, J., Wu, R., Zhang, W., He, S., Li, S., Cheng, Y., & Shi, H. (2023). Vehicle-Mounted Intelligent Unit with Fusion Perception and Collaborative Decision-Making Functions and Control Method. Chinese Invention Patent [CN113954879B].

  21. Ran, B., Li, S., Cheng, Y., Chen, T., Dong, S., Shi, K., Shi, H., & Li, X. (2023). Distributed Driving Systems and Methods for Automated Vehicles. U.S. Patent [US 11,741,834 B2].

  22. Ran, B., Cheng, Y., Chen, T., Yao, Y., Wu, K., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., & Li, X. (2023). Autonomous Vehicle and Cloud Control (AVCC) System with Roadside Unit (RSU) Network. U.S. Patent [US 11,735,035 B2].

  23. Ran, B., Liang, B., Lu, W., Yi, X., Rui, Y., Kong, L., Gong, Y., Shi, K., Cheng, Y., Chen, T., Shi, H., He, S., Yao, Y., Wu, K., & Fu, S. (2023). Virtual Road Configuration Module. Chinese Invention Patent [CN114664116B].

  24. Li, S., Ran, B., Cheng, Y., Chen, Z., He, S., Rui, Y., Li, R., Gu, H., Li, L., Chen, T., Li, X., Dong, S., Shi, K., Shi, H., Yao, Y., Wu, K., & Zhang, X. (2023). Intelligent Roadside Toolbox. Chinese Invention Patent [CN113496602B].

  25. Chen, T., Shi, H., & Yao, Z. (2022). Gasoline Engine Starting Method Combining Variable Fuel Injection Strategy with Exhaust Gas Energy Utilization. Chinese Invention Patent [CN111550322B].

  26. Chen, T., Yao, Z., & Shi, H. (2021). Method for Improving Cold-Start Combustion of a Gasoline Engine with Variable Residual Exhaust Gas Rate. Chinese Invention Patent [CN111550315B].

  27. Shi, H., & Liang, X. (2019). AMT Clutch Friction Plate Rapid Wear Test System and Method. Chinese Invention Patent [CN105606362B].

  28. Shi, H., Wu, Z., Zhang, J., Han, Y., Lan, S., & Liang, X. (2016). AMT Clutch Plate Rapid Wear Testing System. Chinese Utility Model Patent [CN205449493U].

  29. Shi, H., Wu, Z., Han, Y., Lan, S., Zhang, J., & Liang, X. (2016). Vehicle Shock Absorber Vibration Energy Recovery Unit. Chinese Utility Model Patent [CN205123547U].

  30. Shi, H., Wu, Z., Lan, S., Zhang, J., Han, Y., & Liang, X. (2016). Automobile Suspension System Vibration Energy Recovery Unit. Chinese Utility Model Patent [CN205112909U].

  31. Shi, H., Wu, Z., Han, Y., Zhang, J., Lan, S., & Liang, X. (2016). Automobile Suspension System Vibration Energy Recovery Device. Chinese Patent Application [CN105252987A].

  32. Shi, H., Wu, Z., Lan, S., Han, Y., Zhang, J., & Liang, X. (2016). Vehicle Shock Absorber Vibration Energy Recovery Device. Chinese Patent Application [CN105226910A].


标准及建设指南

1.车路协同自动驾驶系统版本建设指南

2.车路协同自动驾驶技术发展路线图研究报告


获奖及荣誉

·2026，《中国公路学报》优秀审稿专家

·2025，上海市晨光学者

·2025，SAE汽车智能交通技术创新奖一等奖（排名6）

·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


主持项目

· 国家自然科学基金优秀青年科学基金项目（海外）- 智能网联交通流建模与控制优化, 2025-2028

· 国家自然科学基金面上项目 - 面向交通智能体训练优化的交通物理世界模型构建方法, 2027-2030

· 国家自然科学基金青年科学基金项目（C类）- 自动驾驶汽车交互解析及效能影响评估, 2026-2028

· 上海市教委晨光计划项目, 2026-2027

· 同济大学青年百人A岗高层次人才科研项目 - 自动驾驶汽车评估测试及决策优化, 2026-2029 

· 重庆理工大学合作项目，2025-2026

· 重庆机电大学合作项目，2026-2027


参与项目

·国家重点研发计划“交通载运装备与智能交通技术”重点专项自主式交通系统计算技术，2023-2027 

·深智城集团交通垂域大模型项目, 2026-2027 

·教育部自动驾驶交通学科突破先导项目, 2025-2029

·基金委卓越研究群体项目“自动驾驶交通智能控制”, 2025-2029

·华为-基于模型预测控制的分层车路协同优化技术合作项目, 2026-2027

·吉利-智驾虚拟主观评价体系构建与验证, 2026-2027

·商飞-机组疲劳状态监测, 2026-2027

·同济—济达仿真AI大模型协同研究合作项目, 2026-2027


过去参与项目

·Rural Autonomous Vehicle Research Program. US. DOT. (15 million. Lead to write the proposal)

·Analysis, Modeling, and Simulation (AMS) Tools for Vehicle Automation. FHWA. Project Manager.

·Realistic Autonomous Vehicle Behavior Investigation for Stakeholder Empowerment. FHWA.

·CPS: Small: NSF-DST: Turning “Tragedy of the Commons (ToC)” into “Emergent Cooperative Behavior (ECB)” for Automated Vehicles at Intersections with Meta-Learning.

·WisTransPortal Maintenance, Planning, and Enhancements: MSN215169, with Wisconsin Department of Transportation and Federal Highway Administration, $475,000 (Research Assistant)

·Wisconsin Statewide Crash Mapping and Analysis Phase 5: MSN217992, with Wisconsin Department of Transportation, $361,632 (Research Assistant)

·Wisconsin DOT TMC Software Phase 4 - NG ATMS Stage 2 Engineering Support: MSN219900, with Wisconsin Department of Transportation, $300,000 (Research Assistant)

·WisTransPortal Maintenance, Planning, and Enhancements: MSN231699, with Wisconsin Department of Transportation, $525,000 (Research Assistant)

·Snow Plow Route Optimization: MSN237025, with Wisconsin Department of Transportation, $75,000 (Research Assistant)

·WisTransPortal Maintenance, Planning, and Enhancements: MSN252342, with Wisconsin Department of Transportation, $515,000 (Research Assistant)

·WisTransPortal Maintenance, Planning, and Upgrades: MSN267552, with Wisconsin Department of Transportation, $515,000 (Research Assistant)

·Wisconsin DOT ATMS Systems Engineering Support: MSN268295, with Wisconsin Department of Transportation, $35,000 (Research Assistant)

·Wisconsin TRCC Traffic Records Data Warehouse: MSN276255, with Wisconsin Department of Transportation and National Highway Traffic Safety Administration, $120,000 (Research Assistant)

·Cooperative R&D of Bus Operation Robust Control System Based on Accurate Information of Computational Vision, International Science and Technology Cooperation Project of Jiangsu Provincial Department of Science and Technology, June 2020 - December 2022, 2.27 Million RMB (Participant). Conduct research.

·PFI-DI Gasoline Engine Performance Research, a Cooperative Project of Tianjin University and United Automotive Electronics Co., Ltd. (Project Assistant).


学术兼职

·《Green Energy and Intelligent Transportation》(Q1, IF=21.5)期刊，青年编委

·IEEE Conference on Automation and AI for Mobility, Connectivity and Sustainability (AIMCS)，副主编 

·Electronics期刊 (Q1) Special Issue: Advanced Control Technologies for Next-Generation Autonomous Vehicles，首席客座编辑

·Expert Systems期刊 (Q2) Special Issue: Safe and Trustworthy Autonomous Systems in Real-World Environments，客座编辑

·IEEE ITSC 2026 Workshop,Topic: Designing & Evaluating AI-empowered Human–AV Interaction, 组织者，主持人.

·国际会议ITFT 2024,2025,2026，程序委员会委员

·AAAI 2026，程序委员会委员

·世界交通运输大会（WTC）智能云管云控、智能网联与车路协同控制、CAV政策法规、智能驾驶出行服务等技术委员会，国际委员

·International Conference on Smart Electrical Grid and Renewable Energy (SEGRE)，指导委员会委员

·担任Transportation Research Part B\C\E、IEEE T-ITS、IEEE TKDE、AAP、ICLR、AAAI等五十余个国际知名期刊和会议，审稿人

· 担任《中国公路学报》“自动驾驶测评关键技术”，专刊组稿专家

·IEEE ITSS，会员

·中国公路学会，高级会员


本研课程

·自动驾驶技术-2026秋季学期

·科技论文写作-2026秋季学期

·智能汽车人机交互-2026秋季学期

·自主式交通技术-2026春季学期

·Autonomous Transportation Systems Technology-2026春季学期


其余兼职

·同济大学启迪书院-2025级13班班主任

·同济大学交通学院-2025级新生导师


招生信息

每年招收多名博士生和硕士生，并长期招收博士后及本科实习生。欢迎具备交通、车辆、计算机、自动化、数学等学科背景，对自动驾驶、智能交通、基础大模型、AI、人机交互等方向感兴趣的同学报考。导师可推荐国（境）外一流学府学习交流工作机会。


其余主页

同济教师主页：https://faculty.tongji.edu.cn/shihaotian/zh_CN

GitHub Profile:  https://haotianshi.github.io/

LinkedIn: https://www.linkedin.com/in/haotian-shi-a718831b0/

Google Scholar: https://scholar.google.com/citations?user=_YbzjdUAAAAJ&hl=en

ResearchGate:  https://www.researchgate.net/profile/Haotian-Shi-9/research



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电话：021-69583650  管理员邮箱：2015qgy@tongji.edu.cn  
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