刘志远，生于山东乳山，教授、博导，获评国家自科基金青A（杰青）、优青。本科毕业于西汉姆联官方网站交通工程专业，博士毕业于新加坡国立大学土木工程系。曾就职于澳大利亚蒙纳士大学土木工程系，任助理教授；2015年全职回到bw必威西汉姆联官方网站任教授、博导，复杂交通网络研究中心主任；2017年12月至2018年1月赴澳大利亚墨尔本大学数学系任访问学者。2019年5月至2023年7月，担任bw必威西汉姆联官方网站副经理，2023年7月至2025年3月担任国家卓越工程师公司副经理。获教育部科学研究优秀成果奖一等奖（排1）、江苏省科学技术奖一等奖（排2）、中国智能交通协会科技进步一等奖（排1）、中国公路学会科技进步一等奖（排1）、华为难题揭榜“火花奖”2项（唯一完成人）、西汉姆联官方网站第十五届“我最喜爱的研究生导师”十佳导师、江苏省双创人才、江苏省青年双创英才、江苏省“333高层次人才培养工程(第二层次)、西汉姆联官方网站“五四青年奖章”等荣誉。

主要研究领域包括交通大数据分析、交通网络规划与管理、多模式网络与公交建模、交通系统仿真等。主持6项国家级课题，在Nature Sustainability、Transportation Science、Transportation Research Part B/Part C/Part E、IEEE Transactions on Knowledge and Data Engineering（TKDE）、European Journal of Operational Research等SCI/SSCI期刊发表论文200余篇，论文被引用1万余次，其中ESI高被引论文10篇。自2021年起连续4年入选“爱思唯尔中国高被引学者”、“全球前2%顶尖科学家”。担任由Elsevier出版的国际期刊Multimodal Transportation执行主编（仅一位），担任Transportation Research Part C、Transportation Research Part E等5个交通研究领域知名SCI期刊副主编。主编交通大数据基础教材书《交通大数据:理论与方法》，入选国家级规划教材，已被40余所高校指定使用;另外出版《交通大数据:存储与计算》《基于手机大数据的交通规划方法与应用》等教材与专著。

主持纵向科研项目（Research Projects, as PI）：

1. 国家自然科学基金杰出青年基金（T2525020），城市复杂交通系统计算与优化，2026/01-2030/12

2. 江苏省科学技术厅，省前沿引领技术基础研究重大项目（攀登项目），交通数字孪生供需平衡计算与仿真优化方法，2023/09-2025/08

3. 国家自然科学基金重点项目，基于大数据的城市道路交通流模型及仿真控制优化方法，2022/01-2026/12

4. 国家自然科学基金优秀青年基金（71922007），多模式交通网络优化与管理，2020/01-2022/12

5. 国家重点研发计划课题（2018YFB1600905），城市多模式交通网络仿真分析软件与系统平台，2019/01-2021/12

6. 国家自然科学基金面上项目（71771050），基于多模式组合出行的新型停车换乘网络设计与优化方法，2018-2021

7. 国家自然科学基金重点项目（51638004），基于广义交通枢纽的城市多模式交通网络协同规划理论与方法--专题二：广义交通枢纽与多模式交通网络环境下的组合出行需求分析理论，2017-2021

8. 国家自然科学基金青年项目（71501038），基于距离的拥堵收费策略对多模式交通网络平衡影响研究，2016-2018

9. 江苏省科技计划青年基金（BK20150603），基于组合出行的城市多模式公交需求分析与网络规划方法研究，2016-2018

Selected SCI/SSCI Papers (*corresponding author)

1. Li, C., Wang, W., Solé-Ribalta, A., Holthoefer, J., Jia, B.*, Liu, Z., et al., 2025. Adaptive capacity for multimodal transport network resilience to extreme floods. Nature Sustainability, 8, 741–752. https://doi.org/10.1038/s41893-025-01575-z

2. Huo, J., Gu, Z., Liu, Z.*, Wang, S., & Laporte, G., 2025. A heteroscedastic robust Bayesian optimization method for solving simulation-based transportation problems. Transportation Science, in press.

3. Gu, Z., Hong, Q., Zhou, Z., Geng, X., Liu, Z.*, & Jia, M., 2025. Topological Information Utilization in Label Enhancement and Label Distribution Learning Based on Optimal Transport Theory. IEEE Transactions on Knowledge and Data Engineering (CCF-A), 37(9), 5666-5678.

4. Zhou, Z., Gu, Z., Liu, P., Yu, W., Liu, Z.*, 2025. Leveraging Semi-Supervised Learning and Meta-Learning for Re-Identification in Difficult Few-Shot Spatiotemporal Anomaly Detection. IEEE Transactions on Neural Networks and Learning Systems, in press.

5. Wang, Z., Liu, Z., Lin, Y., Zhang Y., Cheng Q.*, 2025. Day-to-day Traffic Flow Dynamics with Mixed Autonomy Considering Link-Level Penetration Rate Evolution of Autonomous Vehicles. Proceedings of the IEEE (CCF-A). DOI: 10.1109/JPROC.2025.3562946.

6. Liu, Z., Dong, Y., Zhang, H., Zheng, N*. and Huang, K.*, 2024. A novel parallel computing framework for traffic assignment problem: Integrating alternating direction method of multipliers with Jacobi over relaxation method. Transportation Research Part E, 189, 103687.

7. Mo, P., Liu, Z.*, Tan, Z., Yi, W. and Liu, P., 2024. Subsidy Allocation Problem with Bus Frequency Setting Game: A Trilevel Formulation and Exact Algorithm. Transportation Science, 58(3), 639-663.

8. Cheng, Q., Liu, Z.*, Lu, J., List, G., Liu, P., and Zhou, X.S., 2024. Using frequency domain analysis to elucidate travel time reliability along congested freeway corridors. Transportation Research Part B, 184, 102961.

9. Liu, Z., Xie, S., Zhang, H.*, Zhou, D., Yang, Y., 2024. A Parallel Computing Framework for Large-Scale Microscopic Traffic Simulation Based on Spectral Partitioning. Transportation Research Part E, 103368.

10. Huo, J., Liu, Z.*, Chen, J., Cheng, Q., and Meng, Q., 2023. Bayesian Optimization for Congestion Pricing Problems: A General Framework and Its Instability, Transportation Research Part B, 169, 1-28.

11. Liu, Z., Chen, X.*, Hu, J., Wang, S., Zhang, K., Zhang, H., 2023. An Alternating Direction Method of Multipliers for Solving User Equilibrium Problem. European Journal of Operational Research, 310(3): 1072-1084.

12. Liu, Z., Zhang, H.*, Zhang, K., Zhou, Z., 2023. Integrating Alternating Direction Method of Multipliers and Bush for Solving the Traffic Assignment Problem. Transportation Research Part E, 177, 103233.

13. Wang, J., Zhou, A., Liu, Z.*, Peeta, S., 2024. Robust Cooperative Control Strategy for a Platoon of Connected and Autonomous Vehicles Against Sensor Errors and Control Errors Simultaneously in a Real-World Driving Environment. Transportation Research Part B, 184, 102946.

14. Gu, Z., Li, Y., Saberi, M., and Liu, Z.*, 2024. Simulation-Based Robust and Adaptive Optimization Method for Heteroscedastic Transportation Problems. Transportation Science, 58(4), 860-875.

15. Mo, P., Yao, Y.*, Li, P., Wang, Y., Liu, Z.*, and D'Ariano, A., 2024. Synergising Urban Freight Transportation in Passenger-oriented Transit Corridors: An Efficient Mixed-Integer Linear Programming Approach. Transportation Research Part C, 163, 104644.

16. Huang D., Yang Y., Peng X., Huang J., Mo P., Liu Z.*, Wang S., 2024. Modelling the pedestrian’s willingness to walk on the subway platform: A novel approach to analyze in-vehicle crowd congestion. Transportation Research Part E, 181, 103359.

17. Zhao, H., Guo, T., Tong, W., Yin, H., Liu, Z.*, 2023. PaCS: A Parallel Computation Framework for Field-Based Crowd Simulation. IEEE Transactions on Intelligent Transportation Systems, 24, 11, 12659-12670.

18. Huo, J., Liu, C., Chen, J., Meng, Q., Wang, J., Liu, Z.*, 2023. Simulation-Based Dynamic Origin–Destination Matrix Estimation on Freeways: a Bayesian Optimization Approach. Transportation Research Part E, 173, 103108.

19. Liu, Z.*, Lyu, C., Wang, Z., Wang, S., Liu, P., Meng, Q., 2023. A Gaussian-Process-Based Data-Driven Traffic Flow Model and Its Application in Road Capacity Analysis. IEEE Transactions on Intelligent Transportation Systems, 24(2), 1544-1563.

20. Gu, Z., Li, Y., Saberi, M., Rashidi, T. H., Liu, Z.*, 2023. Macroscopic Parking Dynamics and Equitable Pricing: Integrating Trip-Based Modeling with Simulation-Based Robust Optimization. Transportation Research Part B, 173, 354-381.

21. Gu Z., Yang X., Yu W., Liu Z.*, 2022. TERL: A Two-Stage Ensemble Reinforcement Learning Paradigm for Large-Scale Decentralized Decision Making in Transportation Simulation. IEEE Transactions on Knowledge and Data Engineering (CCF-A), 35, 12, 13043-13054.

22. Yin, R., Liu, X., Zheng, N., & Liu, Z.*., 2022. Simulation-based Analysis of Second-best Multimodal Network Capacity. Transportation Research Part C, 145, 103925.

23. Cheng, Q., Liu, Z.*, Guo, J., Wu, X., Pendyala, R., Belezamo, B., Zhou, X., 2022. Estimating Key Traffic State Parameters Through Parsimonious Spatial Queue Models. Transportation Research Part C, 137, 103596.

24. Ma, J., Meng, Q.*, Cheng, L., and Liu, Z., 2022. General Stochastic Ridesharing User Equilibrium Problem with Elastic Demand, Transportation Research Part B, 162, 162-194.

25. Liu, Z., Lyu, C., Huo, J., Wang, S., and Chen, J.*, 2022. Gaussian Process Regression for Transportation System Estimation and Prediction Problems: The Deformation and a Hat Kernel, IEEE Transactions on Intelligent Transportation Systems.

26. Gu, Z., Wang, Z., Liu, Z., Saberi, M.*, 2022. Network Traffic Instability with Automated Driving and Cooperative Merging. Transportation Research Part C, 138, 103626.

27. Liu, Z.*, Wang, Y., Cheng, Q., and Yang, H., 2022. Analysis of the Information Entropy on Traffic Flows. IEEE Transactions on Intelligent Transportation Systems.

28. Huo, J., Wu, X., Lyu, C., Zhang, W., and Liu, Z.*, 2022. Quantify the road link performance and capacity using deep learning models, IEEE Transactions on Intelligent Transportation Systems, 10, 23, 18581 - 18591.

29. Cheng, Q., Liu, Z.*, Guo, J., Wu, X., Pendyala, R., Belezamo, B., and Zhou, X.*, 2022. Estimating key traffic state parameters through parsimonious spatial queue models. Transportation Research Part C, 137, 103596.

30. Cheng, Q., Liu, Z.*, Lin, Y., and Zhou, X.*, 2021. An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship. Transportation Research Part B. 153, 246-271.

31. Liu, Z.*, Wang, Z., Cheng, Q., Yin, R., and Wang, M., 2021. Estimation of urban network capacity with second-best constraints for multimodal transport systems. Transportation Research Part B, 152, 276-294.

32. Chen, X., Zhang, W., Guo, X., Liu, Z., & Wang, S.*, 2021. An improved learning-and-optimization train fare design method for addressing commuting congestion at CBD stations. Transportation Research Part E, 153, 102427.

33. Liu, Y., Wu, F., Lyu, C., Liu, X., and Liu, Z.*, 2021. Behavior2vector: embedding users’ personalized travel behavior to vector, IEEE Transactions on Intelligent Transportation Systems. DOI: 10.1109/TITS.2021.3078229.

34. Liu, Y., Lyu, C., Liu, Z.*, and Cao, J., 2021. Exploring a Large-scale Multi-modal Transportation Recommendation System, Transportation Research Part C, 126, 103070.

35. Liu, Z.*, Liu, Y., Lyu, C., and Ye, J., 2021. Building Personalized Transportation Model for Online Taxi-hailing Demand Prediction. IEEE Transactions on Cybernetics, 51(9), 4602-4610.

36. Zhang, L., Yuan, Z., Yang, L., and Liu, Z.*, 2020. Recent Developments in Traffic Flow Modeling Using Macroscopic Fundamental Diagram. Transport Reviews, 40(4), 529-550.

37. Gu, Y., Fu, X., Liu, Z.*, Xu, X., and Chen, A., 2020. Performance of transportation network under Perturbations: Reliability, Vulnerability, and Resilience. Transportation Research Part E. DOI: 10.1016/j.tre.2019.11.003.

38. Huang, D., Gu, Y., Wang, S., Liu, Z.*, and Zhang, W., 2020. A Two-phase Optimization Model for the Demand-Responsive Customized Bus Network Design. Transportation Research Part C, 111, 1-21.

39. Liu, Z.*, Liu, Y., Meng, Q., and Cheng, Q., 2019. A Tailored Machine Learning Approach for Urban Transport Network Flow Estimation Based on Cellphone Location and License Plate Recognition Data. Transportation Research Part C, 108, 130-150

40. Liu, Y., Lyu, C., Khadka, A., Zhang, W., and Liu, Z.*, 2019. Spatio-temporal Ensemble Method for Car-Hailing Demand Prediction. IEEE Transactions on Intelligent Transport Systems.

41. Chen, X., Liu, Z.*, Kim, I., 2019. Parallel computing framework for solving user equilibrium problem on computer clusters. Transportmetrica A.

42. Liu, Y., Liu, Z.*, Lyu, C. and Ye, J., 2019. Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-hailing Demand Prediction. IEEE Transactions on Intelligent Transport Systems.

43. Liu, Y., Liu, Z.*, and Jia, R., 2019. DeepPF: A Deep Learning Based Architecture for Metro Passenger Flow Prediction. Transportation Research Part C, 101, 18-34.

44. Cheng, Q., Wang, S., Liu, Z.*, and Yuan, Y., 2019. Surrogate-based Simulation Optimization Approach for Day-to-day Dynamics Model Calibration with Real Data, Transportation Research Part C. 105, 422-438.  

45. Liu, Y., Liu, Z.*, Vu, H., and Lyu, C., 2019. A Spatio-temporal Ensemble Method for Large-Scale Traffic State Prediction. Computer-Aided Civil and Infrastructure Engineering, in press

46. Liu, Z.*, Chen, X., Meng, Q., and Kim, I., 2018. Remote Park-and-Ride Network Equilibrium Model and Its Applications, Transportation Research Part B, 117, 37-62

47. Chen, J., Jia, S., Wang, S.*, and Liu, Z., 2018. Subloop-based reversal of port rotation directions for container liner shipping network alteration, Transportation Research Part B, 118, 336-361.

48. Chen, J., Liu, Z.*, Wang, S., and Chen X., 2018. Continuum approximation modeling of transit network design considering local route service and short-turn strategy, Transportation Research Part E, 119, 165-188.

49. Gu, Z., Shafiei, S., Liu, Z., and Saberi, M.*, 2018. Optimal distance- and time-dependent area-based pricing with the Network Fundamental Diagram, Transportation Research Part C, 95, 1-28.

50. Xing, J., Liu, Z.*, Wu, C. and Chen, S., 2018. Traffic Volume Estimation in Multimodal Urban Networks Using Mobile Phone Location Data, IEEE Intelligent Transport System Magazine.

51. Liu, Z., Wang, S., Huang, K., Chen, J.*, and Fu, Y., 2018. Practical Taxi Sharing Scheme At large Transport Terminals, Transportmetrica B. DOI:10.1080/21680566.2018.1453391

52. Tang, K.*, Chen, S., and Liu, Z., 2018. A Tensor-Based Bayesian Probabilistic Model for Citywide Travel Time Estimation Using Sparse Trajectories. Transportation Research Part C, 90, 260-280.

53. Xu, M., Meng, Q.*, and Liu, Z., 2018. Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment, Transportation Research Part B, 111, 60-82.

54. Huang, D., Liu, Z.*, Fu, X. and Blythe, P.T., 2018. Bus Network Design in a Multimodal Hub-and-Spoke Network Framework. Transportmetrica A. 14(8), 706-735.

55. Tang, K., Chen, S.* and Liu, Z., 2018. Citywide Spatial-temporal Travel Time Estimation Using Big and Sparse Trajectories. IEEE Transactions on Intelligent Transport Systems, 99, 1-12.

56. Gu, Z., Saberi, M.*, Sarvi, M., Liu, Z., 2018. A big data approach for clustering and calibration of link fundamental diagrams for large-scale network simulation applications. Transportation Research Part C, 94, 151-171.

57. Huang, K., Liu, Z.*, Kim, Y., Zhang, Y., Zhu, T., 2018. Analysis of the influencing factors of carpooling schemes. IEEE Intelligent Transportation Systems Magazine. in press.

58. Chen, J., Wang, S., Liu, Z.*, and Guo, Y., 2018. Network-based optimization modeling of manhole setting for pipeline transportation, Transportation Research Part E, 113, 38-55.

59. Liu, Z., Yu, B., Gu, Z.*, Zhong, N., 2018. Intermodal Transportation of Modular Structure Unit, World Review of Intermodal Transportation Research, 7(2), 99-123.

60. Liu, Z.*, Wang, S., Zhou, B., and Cheng, Q., 2017. Robust Optimization of Distance-based Tolls in a Network Considering Stochastic Day to Day Dynamics, Transportation Research Part C, 79, 58-72.

61. Liu, Z.*, Wen, Y., Wang, S. and Chen, J., 2017. On the Uniqueness of User Equilibrium Flow with Speed Limit, Networks and Spatial Economics, 17(3), 763-775.

62. Wang, S., Liu, Z.*, and Qu, X., 2017. Weekly Container Delivery Pattern in Liner Shipping Planning Models, Maritime Policy & Management. DOI: 10.1080/03088839.2017.1295327

63. Chen, J., Wang, S., Liu, Z.*, and Wang, W., 2017. Design of Suburban Bus Route for Airport Access. Transportmetrica Part A, 13(6), 568-589.

64. Huang, D., Liu, Z.*, Liu, P, Chen, J., 2016. Optimal transit fare and service frequency of a nonlinear origin destination-based fare structure, Transportation Research Part E, 96, 1-19.

65. Liu, Z.*, Wang, S., Chen, W. and Zheng, Y., 2016. Willingness to Board: A Novel Concept for Modeling Queuing Up Passengers, Transportation Research Part B, 90, 70-82.

66. Gu, Z., Liu, Z.*, Nirajan S. and Yang, M., 2016. Video-based analysis of school students’ emergency evacuation behavior in earthquakes, International Journal of Disaster Risk Reduction, 18, 1-11.

67. Chen, J., Liu, Z.*, Zhu, S., and Wang, W., 2015. Design of limited-stop bus service with capacity constraint and stochastic travel time, Transportation Research Part E, 83, 1-15.

68. Wang, S.*, Liu, Z., Bell, M., 2015. Profit-based maritime container assignment models for liner shipping networks, Transportation Research Part B, 72, 59-76.

69. Liu, Z. and Bie, Y.*, 2015. Comparison of Hook-turn Scheme with U-turn Scheme Based on the Actuated Traffic Control Algorithm, Transportmetrica A, 11(6), 484-501.

70. Liu, Z.*, Wang, S., Meng, Q., 2014. Optimal Joint Distance and Time Toll for Cordon-based Congestion Pricing, Transportation Research Part B, 69, 81-97.

71. Zheng, Z.*, Liu, Z., Liu, C. and Shiwakoti, N., 2014. Understanding public response to a congestion charge: a random-effects ordered logit approach using revealed and stated preference data, Transportation Research Part A, 70, 117-134.

72. Wang, S., Liu, Z., Meng, Q.*, 2014. Segment-based alteration for container liner shipping network design, Transportation Research Part B, 72, 128-145.

73. Liu, Z.* and Meng, Q., 2014. Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes, International Journal of Systems Science, 45(5), 994-1006.

74. Meng, Q., Liu, Z.* and Wang S., 2014. Asymmetric Stochastic User Equilibrium Problem with Link Capacity Constraints and Elastic Demand, Transportmetrica A. 10(4), 304-326.

75. Liu, Z.*, Meng, Q., Wang S., 2014. Variational inequality model for cordon-based congestion pricing under side constrained stochastic user equilibrium conditions, Transportmetrica A, 10(8), 693-704.

76. Liu, Z., Meng, Q.*, Wang, S., Sun, Z., 2014. Global Intermodal Liner Shipping Network Design, Transportation Research Part E, 61, 28-39.

77. Wang, S., Meng, Q. and Liu, Z.*, 2013. A Note on “Berth Allocation Considering Fuel Consumption and Vessel Emissions, Transportation Research Part E, 49(1), 48-54.

78. Qu, X., Meng, Q. and Liu, Z.*, 2013. Estimation of number of fatalities caused by toxic gases due to fire in road tunnels, Accident Analysis and Prevention,50, 616-621.

79. Wang, S., Meng, Q.*, Liu, Z., 2013. Fundamental properties of volume-capacity ratio of a private toll road in general networks, Transportation Research Part B, 47, 77-86.

80. Wang, S., Meng, Q.* and Liu, Z., 2013. Bunker Consumption Optimization Methods in Shipping: A Critical Review and Extensions, Transportation Research Part E, 53, 49-62.

81. Liu, Z. and Meng, Q.* and Wang, S., 2013. Speed-based Toll Design for Cordon-Based Congestion Pricing Scheme, Transportation Research Part C, 31, 83-98.

82. Wang, S., Meng, Q.*, and Liu, Z., 2013. Containership scheduling with transit-time-sensitive container shipment demand, Transportation Research Part B, 54, 68-83.

83. Liu, Z., Yan, Y.*, Qu, X., and Zhang, Y. 2013. Bus stop-skipping scheme with random travel time, Transportation Research Part C, 35, 46-56.

84. Meng, Q.*, Wang, S. and Liu, Z., 2012. Network Design for Shipping Service of Large-scale intermodal liners, Transportation Research Record, 2269, 42-50.

85. Meng, Q., Liu, Z.* and Wang, S., 2012. Optimal Distance-based Toll Design for Cordon-based Congestion Pricing Scheme with Continuously Distributed Value-of-time, Transportation Research Part E, 48(5), 937-957.

86. Meng, Q.* and Liu, Z., 2012. Mathematical Models and Computational Algorithms for Probit-based Asymmetric Stochastic User Equilibrium Problem with Elastic Demand, Transportmetrica A, 8(4), 261-290.

87. Meng, Q.* and Liu, Z., 2012. Impact Analysis of Cordon-based Congestion Pricing Scheme on Mode-Split of Bimodal Transportation Network, Transportation Research Part C, 21(1), 134-147.

88. Meng, Q.* and Liu, Z., 2011. Trial-and-Error Method for Congestion Pricing Scheme under Side-Constrained Probit-Based Stochastic User Equilibrium Conditions, Transportation, 38(5), 819-843.

近年来投入到交通大数据与机器学习算法方面的研究与工程实践，相关成果被华为集团、中国移动、京沪高速、浙江交投等多家行业龙头部门应用到了20余个大城市与区域的交通大数据实际应用之中。2016年以来，基于在交通大数据算法方面的深度积累，获得21项国内外大数据算法比赛奖项（皆为前三名），包括被誉为“大数据比赛世界杯”的KDD CUP冠军，及其他同为人工智能三大国际顶级赛事的IJCAI冠军、NeurIPS第二名。此外还包括，阿里巴巴天池大赛算法挑战赛冠军、首届滴滴算法大赛-亚军、美国TRB大会数据分析比赛优秀论文奖、CCF大数据与计算智能大赛亚军、Ucar Artificial Intelligence Cup冠军(IEEE computer society)、数字中国创新大赛大数据比赛一等奖等。

欢迎有较强数学建模、统计学、机器学习、计算机编程等方面基础，对科研有深入兴趣的同学报考硕士、博士研究生。长期招收交通网络建模、交通大数据、公共交通等方向的博士后。

联系方式（Contact Info）：

Address：南京市江宁区西汉姆联官方网站路2号  bw必威西汉姆联官方网站（211189）

Email：zhiyuanl@seu.edu.cn