刘杉，1996年出生，东南大学讲师，硕士生导师。2018年本科毕业于北京航空航天大学，保送直博至清华大学，2022年博士毕业。研究领域包括交通系统建模与优化、逆向强化学习、数据挖掘、运筹优化等。主持国家自然科学青年基金、江苏省自然科学基金青年基金，研究成果发表在Transportation Research Part C, Transportation Research Part E等国际知名期刊上，担任IEEE TKDE、IEEE TII、TRE等多本期刊审稿人。


招生计划

每年招收硕士研究生1-2名，欢迎相关专业的同学联系报考。
欢迎本科生参与科研训练，指导数学建模、SRTP、本科毕设、论文专利撰写。

2014.09-2018.06 北京航空航天大学  自动化科学与电气工程学院 学士

2018.09-2022.06 清华大学 工业工程系 博士

中国仿真学会-环境建模仿真专业委员会-委员

中国运筹学会-行为运筹与管理分会-青年理事

中国公路学会-会员

1. Best paper award & best presenter award of the 6th International Symposium on Multimodal Transportation (ISMT, 2024)

2. Best paper award of the 15th International Workshop on Computational Transportation Science (CTS, 2024)

3. 东南大学第20届吾爱吾师-院系最受欢迎老师(2024)

4. 东南大学优秀本科生导师(2023)

5. 江苏省双创博士(2023)

6. 北京市优秀毕业生(2022)

7. 清华大学综合优秀一等奖学金(2022)

5. 中药制药过程控制与智能制造技术全国重点实验室开放课题，基于机器视觉的中药粉体粒度在线检测技术研究与应用，主持

4. 浙江省智能交通工程技术研究中心开放课题，基于深度学习的个性化路径推荐，主持

3. 科技创新2030-“新一代人工智能”重大项目，人机增强的大规模多智能体强化学习理论与应用研究，参与

2. 国家自然科学基金面上项目，基于深度强化学习的多智能体系统智能攻击检测和防御，参与

1. 国家自然科学基金面上项目，非完全合作网络下多无人机分组编队包围控制，参与

[11] Shan Liu, Ya Zhang, Zhengli Wang, Xiang Liu, Hai Yang (2024). Personalized origin–destination travel time estimation with active adversarial inverse reinforcement learning and Transformer. Transportation Research Part E, 193, 103839.

[10] Yanshan Li, Shan Liu*, Ya Zhang, Xiang Liu, Mingyan Xia (2024). A Ladder Water Level Prediction Model for the Yangtze River Based on Transfer Learning and Transformer. IEEE Transactions on Geoscience and Remote Sensing, 62, 4211511.

[9] Pujun Zhang, Dazhou Lei, Shan Liu, Hai Jiang (2024). Recursive logit-based meta-inverse reinforcement learning for driver-preferred route planning. Transportation Research Part E, 185, 103485.

[8] Shan Liu,  Ya Zhang, Zhengli Wang, Hai Yang (2024). Anomalous ride-hailing driver  detection with deep transfer inverse reinforcement learning. Transportation Research Part C, 159, 104466.

[7] Zhenjie Zheng, Zhengli Wang, Shan Liu,  Wei Ma (2024). Exploring the spatial effects on the level of congestion  caused by traffic accidents in urban road networks: A case study of  Beijing. Travel Behaviour and Society, 35, 100728.

[6] Shan Liu,  Ya Zhang, Zhengli Wang, Shiyi Gu (2023). AdaBoost-Bagging deep inverse  reinforcement learning for autonomous taxi cruising route and speed  planning. Transportation Research Part E, 177, 103232.

[5] Pujun Zhang, Shan Liu, Jia Shi, Liying Chen, Shuiping Chen, Jiuchong Gao, Hai Jiang (2023). Route Planning Using Divide-and-Conquer: A Gat Enhanced Insertion Transformer Approach. Transportation Research Part E, 176, 103176.

[4] Shan Liu, Zhengli Wang,  Hai Jiang (2022). Signal timing optimisation with the contraflow left-turn lane design using the cell transmission model. Transportmetrica A, 18(3), 1254-1277.

[3] Shan Liu, Hai Jiang (2022). Personalized route recommendation for ride-hailing with deep inverse reinforcement learning and real-time traffic conditions. Transportation Research Part E, 164, 102780.

[2] Shan Liu, Hai Jiang, Zhe Chen (2021). Quantifying the impact of weather on ride-hailing ridership: Evidence from Haikou, China. Travel Behaviour and Society, 24, 257-269.

[1] Shan Liu, Hai Jiang,   Shuiping Chen, Jing Ye, Renqing He, Zhizhao Sun (2020). Integrating  Dijkstra’s algorithm into deep inverse reinforcement learning for food  delivery route planning. Transportation Research Part E, 142, 102070.