陈勇

陈勇，博士，男，中共党员，浙江丽水人。2025年毕业于浙江大学道路及交通工程专业并获工学博士学位，现为浙江财经大学文华百人计划研究员。主要研究方向为城市计算、出行行为复杂性、时空数据挖掘等，长期聚焦大数据驱动的城市出行模式分析与预测，深入研究时空数据挖掘理论、交通流宏观规律、居民出行决策等关键问题。在Cell子刊Patterns、Cell合作子刊The Innovation、Nature合作子刊npj Sustainable Mobility and Transport、IEEE Transactions on Intelligent Transportation Systems、IEEE Transactions on Computational Social Systems、Transportation Research Part A/C/E、Information Sciences、Knowledge-Based Systems、Frontiers of Engineering Management、Applied Energy等期刊累计发表论文30余篇，谷歌学术总引用900余次，研究成果遴选为Patterns期刊封面以及Patterns作者专访等。作为核心骨干成员参与多项国家自然科学基金项目，授权国家发明专利3项。获浙江大学优秀博士毕业生、浙江省优秀硕士论文、浙江大学竺可桢奖学金(每年全校仅12位研究生获此荣誉)、浙江财经大学卓越之星（每年全校仅2名研究生获此荣誉，1/1800+）等荣誉。目前担任Cell子刊Cell Reports Sustainability、Cell合作子刊The Innovation、IEEE Transactions on Intelligent Transportation Systems、Transportation Research Part C/D/E、Neural Networks等期刊审稿人。

一、科研论文

注：*表示通讯作者，#表示共同第一作者，IF为最新影响因子

[1] Chen Y., Xu H.G., Chen X.M.*, & Gao Z.Y.* A multi-scale unified model of human mobility in urban agglomerations. Patterns, 4(11), 100862, 2023. (Cell子刊, IF = 7.4)

[2] Chen Y.,Chen X.M.*, & Gao Z.Y.* Toward equity, transparency, and collaboration human mobility computing for smart cities. The Innovation, 5(5), 100672, 2024. (Cell合作子刊, IF = 25.7)

[3] Chen Y.,Xie N.K., Xu H.G., Chen X.M.* & Lee D.H. A multi-context aware human mobility prediction model based on motif-preserving travel preference learning. IEEE Transactions on Intelligent Transportation Systems, 25(2), 2139-2152, 2024. (SCI, 智能交通顶刊, JCR-Q1, CCF-B, IF = 8.4)

[4] Chen Y., & Chen X.M.* A novel reinforced dynamic graph convolutional network model with data imputation for network-wide traffic flow prediction. Transportation Research Part C: Emerging Technologies, 143, 103820, 2022. (SCI, 交通运输顶刊, JCR-Q1, IF = 7.9, 入选ITS智能交通协会会刊)

[5] Chen Y.^#, Chi B.^#, Li C.J., Zhang Y.L., Liao C.L., Chen X.M.*, & Xie N.* Towards interactive next location prediction driven by large language models. IEEE Transactions on Computational Social Systems, DOI: 10.1109/TCSS.2024.3522965, 2025. (SCI, JCR-Q1, IF = 4.9, CCF-C)

[6] Chen Y., Chen X.M.*, & Gao Z.Y.* Meet the authors: Yong Chen, Xiqun (Michael) Chen, and Ziyou Gao, Patterns, 4(11), 100877, 2023. (Cell子刊, 特邀专题访谈，IF = 7.4)

[7] Chen Y., Li C.J., Wang W.R., Zhang Y.L., Chen X.M.*, & Gao Z.Y.* Sustainable mobility and transport: Landscape, trends, challenges, and opportunities. npj Sustainable Mobility and Transport, 2, 8, 2025. (Nature合作子刊)

[8] Chen Y., Zhang H.Y., Li C.J., Chi B., Wu J.J.*, & Chen X.M.* Large language model empowered smart city mobility. Frontiers of Engineering Management, 12, 201-207, 2025. (FMS-B, 中科院一区, IF = 7.7)

[9] Chen Y., Wang W.R., & Chen X.M.* Bibliometric methods in traffic flow prediction based on artificial intelligence. Expert Systems with Applications, 228, 120421, 2023. (SCI, JCR-Q1, IF = 7.5)

[10] Liu J.M.^#, Li J.Y.#, Chen Y.^#, ... & Chen X.M.* Multi-scale urban passenger transportation CO2 emission calculation platform for smart mobility management. Applied Energy, 331, 120407, 2023. (SCI, 能源管理顶刊, JCR-Q1, IF = 11.0)

[11] Chen Y., Geng M.S., Zeng J.Q., Yang D., Zhang L., & Chen X.M.* A novel ensemble model with conditional intervening opportunities for ride-hailing travel mobility estimation. Physica A: Statistical Mechanics and its Applications, 628, 129167, 2023. (SCI, JCR-Q2, IF = 3.1)

[12] Chen Y., Zhang S.*, Zhang W.Y., Peng J.J., & Cai Y.S. Multifactor spatio-temporal correlation model based on a combination of convolutional neural network and long short-term memory neural network for wind speed forecasting. Energy Conversion and Management, 185, 783-799, 2019. (SCI, 能源管理顶刊, JCR-Q1, IF = 10.9)

[13] Xiao J.H., Cai Y.S., & Chen Y.* Study on deep reinforcement learning for multi-task scheduling in cloud manufacturing. International Journal of Computer Integrated Manufacturing, doi: https://doi.org/10.1080/0951192X.2025.2452981. (SCI, JCR-Q2, FMS-B, IF = 4.0)

[14] Zhang S., Chen Y., Zhang W.Y.*, & Feng R.J. A novel ensemble deep learning model with dynamic error correction and multi-objective ensemble pruning for time series forecasting. Information Sciences, 544, 427-445, 2021. (SCI, JCR-Q1, IF = 6.8)

[15] Zhang S., Chen Y., & Zhang W.Y.* Spatiotemporal fuzzy-graph convolutional network model with dynamic feature encoding for traffic forecasting. Knowledge-Based Systems, 231, 107403, 2021. (SCI, JCR-Q1, IF = 7.6)

[16] Zhang S., Chen Y., Xiao J.H., Zhang W.Y.*, & Feng R.J. Hybrid wind speed forecasting model based on multivariate data secondary decomposition approach and deep learning algorithm with attention mechanism. Renewable Energy, 174, 688-704, 2021. (SCI, JCR-Q1, IF = 9.1)

[17] Zhang S., Chen Y., Huang X.L.*, & Cai Y.S. Text classification of public feedbacks using convolutional neural network based on differential evolution algorithm. International Journal of Computers Communications & Control, 14(1), 124-134, 2019. (SCI, JCR-Q3, IF = 1.9)

[18] Xia Y.J., Geng M.S, Chen Y., ... & Chen X.M.* Understanding common human driving semantics for autonomous vehicles. Patterns, 4, 100730, 2023. (Cell子刊, 封面论文, IF = 7.4)

[19] Li C.J., Chen Y., Xu H.G., & Chen X.M.* & Lee D.H. Multi-view hypergraph-based ride-sourcing origin-destination demand prediction. IEEE Transactions on Intelligent Transportation Systems, in press. (SCI, 智能交通顶刊, JCR-Q1, CCF-B, IF = 8.4)

[20] Xie N.K., Chen Y., Tang W., & Chen X.M.*. Multi-agent reinforcement learning with communication for ride-sourcing pricing in mixed autonomy mobility. Transportation Research Part C: Emerging Technologies, 176, 105164, 2025. (SCI, 交通运输顶刊, JCR-Q1, IF = 7.9)

[21] Xu H.G., Chen Y., & Chen X.M.*. Understanding ride-sourcing drivers' working patterns based on platform operations data. Transportation Research Part A: Policy and Practice, 194, 104426, 2025. (SCI, 交通运输顶刊, JCR-Q1, IF = 6.8)

[22] Geng M.S., Chen Y., Xia Y.J., & Chen X.M.* Dynamic-learning spatial-temporal transformer network for vehicular trajectory prediction at urban intersections. Transportation Research Part C: Emerging Technologies, 156, 104330, 2023. (SCI, 交通运输顶刊, JCR-Q1, IF = 7.9)

[23] Cai Z.E., Chen Y., Mo D., Liu C.J., & Chen X.M.*. Competition and evolution in ride-hailing market with aggregated services: A dynamic duopoly game model. Transportation Research Part C: Emerging Technologies, 164, 104665, 2024. (SCI, 交通运输顶刊, JCR-Q1, IF = 7.9)

[24] Xu H.G., Chen Y., Li C.J., & Chen X.M.*. Space-time adaptive network for origin-destination passenger demand prediction. Transportation Research Part C: Emerging Technologies, 167, 104842, 2024. (SCI, 交通运输顶刊, JCR-Q1, IF = 7.9)

[25] 郑思静, 陈勇, 朱奕璋, 陈喜群*. 基于个体记忆效应和距离效应的出行目的地识别. 浙江大学学报 (工学版), 58(4), 2024. (EI)

二、主持课题项目

[1] 主持浙江省新苗人才计划项目：360水利卫士——360度全方位的水利工程智能化监管系统(项目号：2020R414041)，2020/01–2020/12

[2] 主持浙江财经大学研究生田野调查基金项目：基于深度学习和迁移学习的短期风速预测系统的研制与推广(项目号：19TYDC030)，2019/05–2020/05

三、授权发明专利

[1] 张帅，陈勇，张文宇，一种交通预测方法及装置，专利号：ZL 202110297442.7

[2] 张帅，张文宇，陈勇，彭娟娟，裘一蕾，一种基于多因素时空相关性的风速预测方法及装置，专利号：ZL 201910115704.6

[3] 张文宇，陈子旋，张帅，陈勇，冯睿隽，一种基于分块矩阵和模糊运输时间的车辆路径优化方法，专利号：ZL 201910526892.1

四、奖励与荣誉

[1] 2025.03  获浙江大学优秀毕业生

[2] 2024.12  获浙江大学竺可桢奖学金（每年全校仅12位研究生获得此荣誉）

[3] 2024.12  获博士研究生国家奖学金

[4] 2022.12  获2021年浙江省优秀硕士学位论文

[5] 2020.12  获硕士研究生国家奖学金

[6] 2019.12  获浙江财经大学“卓越之星”（每年全校仅2名研究生获此荣誉，1/1800+）

[7] 2019.12  获硕士研究生国家奖学金