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基本信息：
于新莲，博士，讲师，硕士生导师，31399金沙娱场城交通运输系
办公地点：东南大学九龙湖校区31399金沙娱场城大楼1004室
联系电话：18262634846
联系方式：xinlianyu@seu.edu.cn
于新莲，31399金沙娱场城交通运输系教师。综合运用运筹与管理科学、机器学习、强化学习、行为科学等理论方法，对交通出行、物流运输等领域的数字化平台协作化运营和管理、公共交通网络设计与动态管控优化、多模式交通与物流网络规划设计等问题开展研究。
目前主持国家自然科学基金青年基金项目1项目，江苏省自然科学基金青年基金项目1项。参与美国能源部高级研究计划1项，美国交通部、国家科学基金（Smart and Connected Communities）、新英格兰地区交通管理局、马萨诸塞公路管理局等机构资助的多项研究项目。在多个国际学术会议如INFORMS年会，世界交通运输大会（WTC）、COTA国际交通科技年会（CICTP）等进行学术报告等。现担任TR Part B/C/E，Transportation，IEEE Transactions-ITS等交通领域重要国际期刊审稿人。
欢迎对科研有深入兴趣，有交通工程、运筹学、统计学、机器学习等方面基础（或者愿意深入学习）的同学报考硕士研究生。
研究方向：
n 方法：动态规划，混合整数规划， 强化学习/机器学习，行为决策科学等
n 应用：交通出行/物流运输数字化平台协作化运营管理，公共交通网络设计与动态管控优化，多模式交通与物流网络规划设计等
教育经历：
2014/09 - 2019/02, 马萨诸塞大学阿默斯特分校, 交通工程, 博士
2014/09 - 2018/05, 马萨诸塞大学阿默斯特分校, 统计学, 硕士
2011/09 - 2014/06, 南京大学, 管理科学与工程, 硕士
2007/09 - 2011/06, 东南大学, 管理学, 学士
工作经历：
2019/03 - 2020/08, 明尼苏达大学双城分校助,博士后研究员
2020/10 - 今, 东南大学, 31399金沙娱场城, 讲师
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
[3].Zhang Z. (lead PI). Leveraging Autonomous Shared Vehicles for Greater Community Health, Equity, Livability, and Prosperity (HELP). Standard Grant (NSF). Sep.2018-Aug.2022. 参与
[4].Ben-Akiva, M. (lead PI) and Gao, S. (UMass PI). Mobility Electronic Market for Optimized Travel (MeMOT). Advanced Research Projects Agency-Energy (ARPA-E), Department of Energy. Nov. 2015 - Sep. 2018. $3,990,128. UMass portion. 参与
[5].Gao, S. (PI). Routing Policy Choice Models in Stochastic Time-Dependent Networks: The Stockholm Case Study. US Department of Transportation through New England University Transportation Center.参与
[6].Gao, S. (PI). An Optimal Adaptive Routing Algorithm for Large-Scale Stochastic Time Dependent Networks. US Department of Transportation through New England University Transportation Center. 2015.参与
代表性论文：
[1].Xinlian Yu; Alireza Khani; Jingxu Chen; Hongli Xu; Haijun Mao. Real-time Holding Control for Transfer Synchronization via Robust Multi-agent Reinforcement Learning, IEEE Transactions on Intelligent Transportation Systems, 2022 (Forthcoming, DOI 10.1109/TITS.2022.3204805)
[2].Yuhao Wang#; Hongli Xu; Xinlian Yu; Jing Zhou. Heuristic Feeder-bus Operation Strategy Considering Weather Information: A Chance-constrained Model.International Transactions in Operational Research, 2022 (Forthcoming)
[3].Xinlian Yu*; Song Gao. A Batch Reinforcement Learning Approach to Vacant Taxi Routing, Transportation Research Part C: Emerging Technologies, 139(2022):103640
[4].Yanqiu Cheng#; Xianbiao Hu; Kuanmin Chen; Xinlian Yu; Yulong Luo. Online Longitudinal Trajectory Planning for Connected and Autonomous Vehicles in Mixed Traffic Flow with Deep Reinforcement Learning Approach, Journal of Intelligent Transportation Systems, 2022 Feb 24:1-5.
[5].Tien Mai; Xinlian Yu*; Song Gao; Emma Frejinger. Routing Policy Choice Prediction in a Stochastic Network: Recursive Model and Solution Algorithm, Transportation Research Part B: Methodological, 2021, 151: 42-58
[6].Xinlian Yu; Song Gao; Xianbiao Hu; Hyoshin Park. A Markov Decision Process Approach to Vacant taxi routing with E-hailing, Transportation Research Part B: Methodological, 2019, 121:114-134
[7].Xinlian Yu; Song Gao. Learning Routing Policies in a Disrupted, Congestible Network with Real-time Information: An Experimental Approach, Transportation Research Part C: Emerging Technologies, 2019, 106: 205-219
[8].徐红利; 于新莲*; 周晶. 诱导信息下考虑路段容量退化的流量演化研究,管理科学学报,2015,(07):39-47
(*通讯，#学生合作者)
近期会议报告：
[1].Xinlian, Yu; Vehicle routing in mobility-on-demand systems via a batch reinforcement learning approach, The 22nd COTA International Conference of Transportation Professionals (CICTP 2022), Changsha, China, Virtual Meeting, July 8-11, 2021
[2].Xinlian Yu; Song Gao; Optimal Routing of Multiple Vacant Taxis: A Policy Gradient Method with Endogenous State Transition Probabilities, The 100th Annual Meeting of Transportation Research Board Compendium of Papers. Virtual Meeting, Jan.25-29, 2021
[3]. Xinlian Yu; Alireza Khani; Real-time Transit Control for Transfer Synchronization with Deep Reinforcement Learning Transportation Research Board, The 100th Annual Meeting of Transportation Research Board Compendium of Papers. Virtual Meeting, Jan. 25-29, 2021
[4].Xinlian Yu; Song Gao; A Model-free Batch Reinforcement Learning Approach for Vacant Taxi Routing with E-hailing, The 24th International Conference of Hong Kong Society for Transportation Studies, Hong Kong, Dec.14-16, 2019
[5]. Xinlian Yu; Alireza Khani; Operation of Shared Autonomous Vehicle Systems: Optimal Fleet Sizing and Depot Deployment, 2019 INFORMS Annual Meeting, Seattle, Oct.10-23, 2019
[6]. Xinlian Yu; Song Gao; Optimizing Vacant Taxis Routing Decisions: Model-based and Model -free Approaches, The 98th Annual Meeting of Transportation Research Board Compendium of Papers., Washington, DC, Jan.13-17, 2019
其他：
[1]. 指导本科生获2022年第七届江苏省交通科技大赛三等奖
[2]. 指导研究生获2021年第十八届中国研究生数学建模竞赛二等奖
[3]. Travel award, the International Association for Travel Behavior Research (IATBR)，2018.07
[4]. The 2nd place finalist, the North American Regional Science Council (NARSC) Graduate Student Paper Competition，2017.11
