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基本信息：于新莲，博士，副教授，硕导
所属系所：交通运输系
办公地点：东南大学九龙湖校区交通学院大楼1004室
联系电话：18262634846
联系方式：xinlianyu@seu.edu.cn
主要研究方向：交通与物流网络建模与优化，需求响应式交通与物流系统动态运营优化，城市公共交通系统动态管控优化等。主持国家自然科学基金、江苏省自然科学基金等项目，参与美国能源部高级研究计划、交通部、国家科学基金、新英格兰地区交通管理局等机构资助的多项研究项目。担任TR Part B/C/E，Transportation，IEEE T ITS等交通领域期刊审稿人。
欢迎对科研有深入兴趣，有交通运输、运筹优化、统计学、机器学习等方面基础（或者愿意深入学习）的同学报考研究生。
研究方向
研究方法：动态规划，混合整数规划，随机优化，强化学习/机器学习等
研究问题：需求响应式交通运营管理，交通与物流网络优化，低空物流等
教育经历
2014-09 至 2019-02, 马萨诸塞大学阿默斯特分校, 交通工程, 博士
2014-09 至 2018-05, 马萨诸塞大学阿默斯特分校, 统计学, 硕士
2011-09 至 2014-06, 南京大学, 管理科学与工程, 硕士
2007-09 至 2011-06, 东南大学, 管理学, 学士
工作经历
2024.4 至 今, 东南大学, 交通学院, 副教授
2020.10 至 2024.3, 东南大学, 交通学院, 讲师
2019.03 至 2020.08, 明尼苏达大学双城分校,博士后
科研项目
1.国家自然科学基金青年项目，考虑供需交互变化的网约车非短视动态调度优化研究，2023-2025，主持
2.江苏省自然科学基金青年项目，面向耦合需求的网约车订单匹配与巡游路径优化研究, 2021-2024，主持
学术成果
一作/通讯论文
1.Yu, X., Hua, M., Chen, J., Peng, J., Hua, M. (2025). Uncovering Passenger-seeking Behavior of Vacant Taxis from Trajectory Data via Self-supervised Deep Spectral Clustering. IEEE Transactions on Intelligent Transportation Systems, 26(4).
2.Yu, X., Chen, J., Kumar, P., Khani, A., & Mao, H. (2024). An integrated optimisation framework for locating depots in shared autonomous vehicle systems. Transportmetrica A: Transport Science, 20(2), 2152299.
3.Yao, H., Yu, X.*, Mao, H., Bai, D., & Zhang, S. (2024). The spatial spillover impact and transmission mechanisms of logistics agglomeration on eco-efficiency: A case study in China. Energy, 308, 132826.
4.Yu, X., Zhu, Z., Mao, H., Hua, M., Li, D., Chen, J., & Xu, H. (2023). Coordinating matching, rebalancing and charging of electric ride-hailing fleet under hybrid requests. Transportation Research Part D: Transport and Environment, 123, 103903.
5.Yu, X., Khani, A., Chen, J., Xu, H., & Mao, H. (2022). Real-time holding control for transfer synchronization via robust multiagent reinforcement learning. IEEE Transactions on Intelligent Transportation Systems, 23(12), 23993-24007.
6.Yu, X., & Gao, S. (2022). A batch reinforcement learning approach to vacant taxi routing. Transportation Research Part C: Emerging Technologies, 139, 103640.
7.Mai, T., Yu, X.*, Gao, S., & Frejinger, E. (2021). Routing policy choice prediction in a stochastic network: Recursive model and solution algorithm. Transportation Research Part B: Methodological, 151, 42-58.
8.Yu, X., Gao, S., Hu, X., & Park, H. (2019). A Markov decision process approach to vacant taxi routing with e-hailing. Transportation Research Part B: Methodological, 121, 114-134.
9.Yu, X., & Gao, S. (2019). Learning routing policies in a disrupted, congestible network with real-time information: An experimental approach. Transportation Research Part C: Emerging Technologies, 106, 205-219.
其他论文
1.Hua, M., Yu, X., Chen, X., Chen, J., & Cheng, L. (2025). Can bike sharing achieve self-balancing distribution? Evidence from dockless and station-based cases. Travel Behaviour and Society, 38, 100879.
2.Dong, C., Xiong, Z., Li, N., Yu, X., Liang, M., Zhang, C., & Wang, H. (2025). A real-time prediction framework for energy consumption of electric buses using integrated Machine learning algorithms. Transportation Research Part E: Logistics and Transportation Review, 194, 103884.
3.Yu, S., Peng, J., Ge, Y., Yu, X., Ding, F., Li, S., & Ma, C. (2024). A traffic state prediction method based on spatial–temporal data mining of floating car data by using autoformer architecture. Computer‐Aided Civil and Infrastructure Engineering, 39(18), 2774-2787.
4.Liu, Y., Xu, H., Yu, X., & Zhou, J. (2024). Heuristic feeder‐bus operation strategy considering weather information: a chance‐constrained model. International Transactions in Operational Research, 31(4), 2446-471.
5.Shen, X., Chen, J., Zhu, S., & Yu, X. (2024). A data-driven inspection method for identifying container bookings with concealed hazardous materials. Engineering Optimization, 56(9), 1361-1381.
6.Cheng, Y., Hu, X., Chen, K., Yu, X., & Luo, Y. (2023). Online longitudinal trajectory planning for connected and autonomous vehicles in mixed traffic flow with deep reinforcement learning approach. Journal of Intelligent Transportation Systems, 27(3), 396-410.
专利
于新莲；张潜力；毛海军；陈景旭；董长印. 一种适用于低密度人口的乡村快递配送站选址方法.申请号 202111367251X
于新莲；张潜力；毛海军；陈景旭；董长印.一种港口型物流枢纽产业集群发展状况评估方法.申请号2021114609265
课程教学
本科专业课《物流系统规划与设计》
本科专业基础课《人工智能基础》
研究生课程《物流系统优化与仿真》
