2019年3月—2023年4月，博士，荷兰代尔夫特理工大学（TU Delft），交通工程

2015年9月—2018年8月，硕士/工程师学位，法国国立高等先进技术公司（ENSTA-Paris），应用数学

2011年9月—2015年6月，学士，南京大学，物理学

2025年11月—至今，西汉姆联官方网站，bw必威西汉姆联官方网站，（上岗）副研究员

2024年5月—2025年10月，荷兰代尔夫特理工大学，认知机器人系，博士后

聚焦于研究自动驾驶决策与规划、自动驾驶安全评估与改进、强化学习算法。

欧盟EU Horizon 2020 Epistemic AI（E-Pi）认知人工智能项目。

1. Li G, Spaan M T J, Kooij J F P. Off-Policy Safe Reinforcement Learning with Cost-Constrained Optimistic Exploration[C]//International Conference on Learning Representations (ICLR). 2026. Poster.

2. Li G, Li Z, Knoop V L, van Lint J W C. How Far Ahead Should Autonomous Vehicles Start Resolving Predicted Conflicts? Exploring Uncertainty-Based Safety-Efficiency Trade-Off[J]. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(10): 14183-14195. DOI: 10.1109/TITS.2024.3393641.

3. Li G, Jiao Y, Calvert S C, van Lint J W C. Lateral conflict resolution data derived from Argoverse-2: Analysing safety and efficiency impacts of autonomous vehicles at intersections[J]. Transportation Research Part C: Emerging Technologies, 2024, 167: 104802. DOI: 10.1016/j.trc.2024.104802.

4. Nguyen T T, Calvert S C, Li G, et al. Interpretable Representation and Customizable Retrieval of Traffic Congestion Patterns Using Causal Graph-Based Feature Associations[J]. Data Science for Transportation, 2024, 6(3): 18. DOI: 10.1007/s42421-024-00106-0.

5. Jiao Y, Li G, Calvert S C, van Cranenburgh S, van Lint H. Beyond behavioural change: Investigating alternative explanations for shorter time headways when human drivers follow automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2024, 164: 104673. DOI: 10.1016/j.trc.2024.104673.

6. Li G, Li Z, Knoop V L, van Lint H. Unravelling uncertainty in trajectory prediction using a non-parametric approach[J]. Transportation Research Part C: Emerging Technologies, 2024, 163: 104659. DOI: 10.1016/j.trc.2024.104659.

7. Li G, Knoop V L, van Lint H. How predictable are macroscopic traffic states: a perspective of uncertainty quantification[J]. Transportmetrica B: Transport Dynamics, 2024, 12(1): 2314766. DOI: 10.1080/21680566.2024.2314766.

8. Li G, Jiao Y, Knoop V L, Calvert S C, van Lint J W C. Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles[C]//2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023: 5818-5823. DOI: 10.1109/ITSC57777.2023.10422574.

9. Li Z, Gong C, Lin Y, Li G, Wang X, Lu C, Wang M, Chen S, Gong J. Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges[J]. Green Energy and Intelligent Transportation, 2023, 2(4): 100103. DOI: 10.1016/j.geits.2023.100103.

10. Shiomi Y, Li G, Knoop V L. Analysis of Stochasticity and Heterogeneity of Car-Following Behavior Based on Data-Driven Modeling[J]. Transportation Research Record: Journal of the Transportation Research Board, 2023, 2677(12): 604-619. DOI: 10.1177/03611981231169279.

11. Li G, Knoop V L, van Lint H. Estimate the limit of predictability in short-term traffic forecasting: An entropy-based approach[J]. Transportation Research Part C: Emerging Technologies, 2022, 138: 103607. DOI: 10.1016/j.trc.2022.103607.

12. Li G, Knoop V L, van Lint J W C. Multistep traffic forecasting by dynamic graph convolution: Interpretations of real-time spatial correlations[J]. Transportation Research Part C: Emerging Technologies, 2021, 128: 103185. DOI: 10.1016/j.trc.2021.103185.

13. Li G, Knoop V L, van Lint H. Dynamic Graph Filters Networks: A Gray-box Model for Multistep Traffic Forecasting[C]//2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2020: 1-6. DOI: 10.1109/ITSC45102.2020.9294627.

博士cum laude荣誉毕业（4%），2023年

《高级运筹学》，硕士课程

IEEE Transactions on ITS、Transportation Research Part C等期刊审稿人

长期招收从事强化学习、机器视觉研究的硕士研究生。欢迎具备交通工程、计算机、自动化、应用数学等相关背景的员工通过邮箱联系！