[3]   2018-11 至 2019 年 11 月，University of Washington (Seatle)华盛顿大学，Urban design and planning， Visiting Scholar [4]   2023-07 至 2023 年 08 月，The Hong Kong Polytechnic University (PolyU)香港理工大学，Department of Civil and Environmental Engineering， Visiting Scholar Jinlei Zhang , Hongshu Che, Feng Chen*, Wei Ma, Zhengbing He. Short-term origin-destination demand prediction in urban rail transit systems: a channel-wise attentive split-convolutional neural network method[J]. Transportation Research Part C: Emerging Technologies , 2021, 124: 102928. (SCI ，中科院 1 区 ) Jinlei Zhang, Feng Chen*, Zhiyong Cui, Yinan Guo, Yadi Zhu. Deep learning architecture for short-term passenger flow forecasting in urban rail transit[J]. IEEE Transactions on Intelligent Transportation Systems , 2021, 22(11): 7004-7014. (SCI ，中科院 1 区 ) Jiateng Yin*, Miao Wang, Andrea D’Ariano, Jinlei Zhang* , Lixing Yang. Synchronization of train timetables in an urban rail network: A bi-objective optimization approach [J]. Transportation Research Part E: Logistics and Transportation Review , 2023, 174: 103142. (SCI ，中科院 1 区 ) Jinlei Zhang, Feng Chen, Lixing Yang*, Wei Ma*, Guangyin Jin, Ziyou Gao. Network-wide link travel time and station waiting time estimation using automatic fare collection data: a computational graph approach[J]. IEEE Transactions on Intelligent Transportation Systems ，2022. (SCI ，中科院 1 区 ) Yongjie Yang, Jinlei Zhang* , Lixing Yang, Yang Yang, Xiaohong Li, Ziyou Gao. Short-term passenger flow prediction for multi-traffic modes: A Transformer and residual network based multi-task learning method[J]. Information Sciences , 2023. (SCI ，中科院 1 区 ) Guangyin Jin, Min Wang, Jinlei Zhang, Hengyu Sha, Jincai Huang*. STGNN-TTE: Travel time estimation via spatial-temporal graph neural network[J]. Future Generation Computer Systems , 2022, 126: 70-81. (SCI ，中科院 1 区 ) Guangyin Jin, Fuxian Li, Jinlei Zhang, Mudan Wang, Jincai Huang*. Automated dilated spatio-temporal synchronous graph modeling for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems , 2022. (SCI ，中科院 1 区 ) Shuxin Zhang, Jinlei Zhang*, Lixing Yang, Jiateng Yin, Ziyou Gao. Spatiotemporal attention fusion network for short-term passenger flow prediction on New Year’s Day holiday in urban rail transit system [J]. IEEE Intelligent Transportation Systems Magazine , 2023. (SCI ，中科院 3 区 ) Jinlei Zhang , Hua Li, Shuxin Zhang, Lixing Yang*, Guangyin Jin*, Jianguo Qi. STG-GAN: A spatiotemporal graph generative adversarial networks for short-term passenger flow prediction in urban rail transit systems[J]. International Journal of General Systems , 2023. (SCI ，中科院 3 区 ) Jinlei Zhang, Feng Chen*, Qing Shen. Cluster-based LSTM network for short-term passenger flow forecasting in urban rail transit[J]. IEEE Access, 2019, 7: 7147653-147671. (SCI ，中科院 3 区 ) Jinlei Zhang, Feng Chen*, Zijia Wang, Hanxiao Liu. Short-term origin-destination forecasting in urban rail transit based on attraction degree[J]. IEEE Access, 2019, 7: 7133452-133462. (SCI ，中科院 3 区 ) Jinlei Zhang, Feng Chen*, Yinan Guo, Xiaohong Li. Multi-graph convolutional network for short-term passenger flow forecasting in urban rail transit[J]. IET Intelligent Transport Systems , 2020, 14(10): 1210-1217. (SCI ，中科院 4 区 ) Feng Chen, Jinlei Zhang*, Zijia Wang, Shunwei Shi, Haixu Liu. Passenger travel characteristics and bus operational states: a study based on IC card and GPS data in Yinchuan, China[J]. Transportation Planning and Technology , 2019, 42(8): 825-847. (SCI ，中科院 4 区 ) Jinlei Zhang, Feng Chen, Zijia Wang*, Rui Wang, Shunwei Shi. Spatiotemporal patterns of carbon emissions and taxi travel using GPS data in Beijing[J]. Energies, 2018, 11(3): 500. (SCI ，中科院 4 区 ) 张金雷 , 陈瑶, 杨立兴, 李华, 阴佳腾*. 基于计算机视觉的轨道交通站内客流识别与预测[J]. 铁道科学与工程学报, 2023. (EI) 张金雷 ， 陈奕洁，Panchamy Krishnakumari，金广垠*，王骋程，杨立兴.基于注意力机制的城市轨道交通网络级多步短时客流时空综合预测模型[J]. 地球信息科学学报, 2023. (EI) 陈峰*， 张金雷， 王子甲. 铁路小半径曲线外轨侧磨影响因素分析[J]. 铁道科学与工程学报, 2018, 15(07): 1678-1684. (EI) 金广垠，沙恒宇， 张金雷 * ，黄金才. 基于路段-路口联合建模的对偶图卷积网络的行程时间估计方法[J]. 地球信息科学学报，2023. (EI) 戚建国, 周亚茹, 杨立兴, 张金雷 , 邸振. 客货共运模式下高铁列车货运兼办方案优化. 北京交通大学学报, 2023. Xuemei Wang, Ying Chen, Jinlei Zhang* . Urban road average speed prediction method based on GCN[J]. Transportation Research Record , 2023. (SCI ，中科院4区) Jinlei Zhang , Shuai Mao, Lixing Yang*, Wei Ma, Shukai Li, Ziyou Gao*, Physics-informed deep learning for traffic state estimation based on the traffic flow model and computational graph method[J]. Information Fusion , 2023. (SCI, IF:18.6，中科院1区) Shuxin Zhang, Jinlei Zhang* , Lixing Yang, Chengcheng Wang, Ziyou Gao. COV-STFormer for short-term passenger flow prediction during COVID19 in urban rail transit systems[J]. IEEE Transactions on Intelligent Transportation Systems , 2023. (SCI, 中科院1区) Kuo Han, Jinlei Zhang* , Xiaopeng Tian, Chunqi Zhu, Songsong Li. Meta-Learning Based Passenger Flow Prediction for Newly-Operated Stations[J]. GeoInformatica , 2023. (SCI, 中科院4区) Yijie Chen, Jinlei Zhang* , Yuan Lu, Hanxiao Liu, Ying Liang. MSFPF：A Multi-stage Fusion Framework for Short-term Passenger Flow Forecasting in URT Systems Using Multi-Source Data[J]. Transportation Research Record , 2023. (SCI ，中科院4区) Yongjie Yang, Jinlei Zhang* , Lixing Yang, Ziyou Gao. Network-wide short-term inflow prediction of the multi-traffic modes system: An adaptive multi-graph convolution and attention mechanism based multitask-learning model[J]. Transportation Research Part C: Emerging Technologies , 2024, 158: 104428. (SCI ，中科院 1 区 ) Jinlei Zhang , Ergang Shan, Lixia Wu, Jiateng Yin*, Lixing Yang*, Ziyou Gao. An End-to-end predict-then-optimize clustering method for stochastic assignment problems[J]. IEEE Transactions on Intelligent Transportation Systems , 2024. (SCI, 中科院1区) Shuxin Zhang, Jinlei Zhang* , Lixing Yang, Shukai Li, Ziyou Gao. Physics Guided Deep Learning-based Model for Short-term Origin-Destination Demand Prediction in Urban Rail Transit Systems during COVID-19[J]. Engineering , 2024. (SCI，IF:12.8，中科院1区)
Xiaohui Zhong, Jinlei Zhang* , Qiang Hua, Lixing Yang, Ziyou Gao . Short-Term Origin-Destination Demand Prediction Based on Spatiotemporal Encoder-Decoder Network with a Residual Feature Extractor[J]. Transportation Research Record , 2024. (SCI，中科院4区) 张金雷， 杨健 ， 刘晓冰 ，陈瑶 ， 杨立兴 ， 高自友. 基于计算机视觉的轨道交通站内火灾检测与定位[J]. 交通运输系统工程与信息，2024 . (EI) Entai Wang, Lixing Yang, Jiateng Yin, Jinlei Zhang ，Ziyou Gao. Passenger-oriented rolling stock scheduling in the metro system with multiple depots: Network flow based approaches[J]. Transportation Research Part B: Methodological , 2024, 180: 102885. (SCI, 中科院1区) Yunfeng Zhang, Shukai Li, Yin Yuan, Jinlei Zhang , Lixing Yang. Approximate dynamic programming approach to efficient metro train timetabling and passenger flow control strategy with stop-skipping[J]. Engineering Applications of Artificial Intelligence , 2024, 127: 107393. (SCI, 中科院1区)
Pengfei Cui, Xiaobao Yang, Mohamed Abdel-Aty, Jinlei Zhang , Xuedong Yan. Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning[J]. Accident Analysis & Prevention , 2024, 200: 107564. (SCI, 中科院1区)
张金雷 , 杨咏杰, 李华, 杨立兴, 阴佳腾*. 基于时空生成对抗网络的城市轨道交通短时客流预测[J]. ChinaXiv.202210.00100.V1, 2022. [2] 陈峰, 张金雷 , 李小红, 朱亚迪, 胡舟. 基于图卷积神经网络的轨道交通短时客流预测方法和系统: 中国, CN202010316862.0[P], 2020-04-21. [3] 陈峰, 张金雷 , 李小红, 朱亚迪, 王蕊. 一种基于深度学习的OD客流预测方法: 中国, CN202010861302.3[P], 2020-08-25. [4] 张金雷 , 杨立兴, 李华, 戚建国, 阴佳腾, 陈瑶, 高自友. 一种基于生成对抗网络的城市轨道交通短时客流预测方法: 中国, CN202210188660.1[P], 2022-02-28. [5] 张金雷 , 韩阔, 朱春琪, 李小红, 李松松, 黄晓宇. 一种基于元学习的地铁新开车站短期客流预测方法: 中国, CN202210735898.1[P], 2022-06-27. [6] 张金雷 , 杨立兴, 章树鑫, 徐猛, 李克平, 李小红, 高自友. 一种考虑疫情因素的城市轨道交通短时客流预测方法, 中国, CN202310001447.X[P], 2023-1-3. [7] 张金雷 , 杨立兴, 杨咏杰, 阴佳腾, 戚建国, 高自友. 基于自适应多图卷积的多模式交通系统短时客流预测方法, 中国, CN202310108449.9[P], 2023-2-1. [8] 张金雷 , 杨立兴, 陈奕洁, 李小红, 高自友. 基于注意力机制的城市轨道交通多步短时客流预测方法: 中国, CN202211660412.9[P], 2022-12-23. [9] 杨立兴, 张金雷 , 杨咏杰, 阴佳腾, 高自友. 一种基于深度学习的网络级多模式交通短时客流预测方法: 中国, CN202211660409.7[P], 2022-12-23. [10] 张金雷 , 杨立兴, 单尔刚, 吴黎霞, 高自友. 一种基于预测与决策一体化的快递系统智能订单分配方法: 中国, CN202211526434.6[P], 2022-12-01. [10] 张金雷 , 金广垠, 杨立兴, 沙恒宇, 黄金才, 杨咏杰, 高自友. 基于路口联合建模的对偶图卷积网络的行程时间估计方法: 中国, CN202211622742.9[P], 2022-12-17. [12] 张金雷, 梁莹, 陈奕洁，杨立兴, 杨洋, 高自友. 一种基于多源数据的多层融合城市轨道交通客流预测方法: 中国, CN202310610756.7 [P], 2023-05-26.