刘志远
教授
办公室:
邮箱:zhiyuanl@seu.edu.cn
刘志远,生于山东乳山,东南大学首席教授、博导,获评国家自科基金青A(杰青)、优青。本科毕业于东南大学交通工程专业,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年全职回到东南大学交通学院任教授、博导;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,担任交通学院副院长,2023年7月至2025年3月担任国家卓越工程师学院副院长。目前担任东南大学统计与数据科学学院直属党支部书记、复杂交通网络研究中心主任,兼任国务院学位委员会交通运输工程学科评议组成员。 主持国家自科基金重点项目(2项)、重点研发计划课题等7项国家级科研课题。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)、东南大学第十五届“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)”、东南大学“五四青年奖章”等荣誉。
教育背景

本科毕业于东南大学交通工程专业,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年全职回到东南大学交通学院任教授、博导,复杂交通网络研究中心主任;201712月至20181月赴澳大利亚墨尔本大学数学系任访问学者。20195月至20237月,担任交通学院副院长,20237月至20253月担任国家卓越工程师学院副院长。


工作经历
研究领域

    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。主持国家自科基金重点项目(2项)、重点研发计划课题等7项国家级科研课题。以第一或通讯作者Nature SustainabilityINFORMS Journal on ComputingIEEE TKDETransportation ScienceTransportation Research Part B/Part C/Part E、等知名SCI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13篇。连续5年入选爱思唯尔中国高被引学者”“全球前2%顶尖科学家。担任交通领域知名SCI期刊TR Part C领域主编Part E副主编Elsevier出版的国际期刊Multimodal Transportation执行主编(仅一位)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。

科研项目

主持纵向科研项目(Research Projects, as PI):

1. 国家自然科学基金重点项目(72631003),需求响应式城市公交系统规划与运营管理,2027/01-2031/12

2. 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

3. 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

4. 国家自然科学基金重点项目52131203,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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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


发明专利
学术著作
学术论文

Selected SCI/SSCI Papers (*corresponding author)

1. Hu, Z., Liu, Z.*, Huang, D., Wang, S., & Mo, P. 2026. A Trilevel Programming Model and Nested Generalized Benders Decomposition for the Bus LineContracting Problem.INFORMS Journal on Computing. https://doi.org/10.1287/ijoc.2025.1527.

2. Wang, Z, Liu, C, Xin, Y, Zhang, Y, Huang, K, Cheng, Q, Zhang, Y, Li, X, Zhang, Y, Liu, Y, Jiang, W.*, & Liu, Z.* 2026. Urban energy and transport impacts of autonomous Robotaxi deployment, Nature Sustainability, in press.

3. 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.

4. 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, 59(6), 1353-1374.

5. 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.

6. 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,36(11),19560-19573. DOI: 10.1109/TNNLS.2025.3578642.

7. 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.

8. 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 PartE, 189, 103687.

9. 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.

10. 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.

11. 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.

12. 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.

13. 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.

14. 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.

15. 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.

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

17. 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.

18. 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.

19. 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.

20. 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.

21. 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.

22. 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.

23. 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.

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

25. 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.

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

27. 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.

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

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

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

31. 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.

32. 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.

33. 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.

34. 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.

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

36. 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.

37. 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.

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

39. 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.

40. 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.

41. 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.

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

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

44. 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.

45. 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.

46. 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.

47. 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, 35(1), 26-44.

48. 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.

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

50. 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.

51. 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.

52. 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.

53. 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

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

55. Xu, M., Meng, Q.*, andLiu, 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.

56. 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.

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

58. 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.

59. Huang, K.,Liu, Z.*, Kim, Y., Zhang, Y., Zhu, T., 2018. Analysis of the influencing factors of carpooling schemes.IEEE Intelligent Transportation Systems Magazine, 11(3), 200-208.

60. 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.

61. 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.

62. 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.

63. 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.

64. 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

65. 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.

66. 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.

67. 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.

68. 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.

69. 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.

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

71. 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.

72. 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.

73. 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.

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

75. 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.

76. 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.

77. 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.

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

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

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

81. 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.

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

83. 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.

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

85. 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.

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

87. 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.

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

89. Meng, Q.*andLiu, 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.

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荣誉奖项

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。


教授课程
学术兼职
招生需求

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:南京市江宁区东南大学路2号 东南大学交通学院(211189

Email: zhiyuanl@seu.edu.cn