基本信息：
刘志远，东南大学青年首席教授，博士研究生导师。2007年毕业于东南大学交通工程专业，获学士学位。2011年毕业于新加坡国立大学土木工程系，获博士学位，并随后留校进行博士后研究一年。2012至2015年，就职于澳大利亚蒙纳士大学土木工程系，任助理教授，在澳期间作为主导师曾指导四名博士生、一名访问学者。2015年全职回到31399金沙娱场城任教授、博导。2017年12月至2018年1月，澳大利亚墨尔本大学数学系访问学者。目前担任国家卓越工程师学院副院长，复杂交通网络研究中心主任，澳大利亚蒙纳士大学客座教授。2020年获国家自然科学基金优秀青年科学基金资助、获江苏省双创人才、江苏省青年双创英才、东南大学“五四青年奖章”、2022年度中国智能交通协会优秀科技创新领军人才奖、江苏省科学技术二等奖2项、华夏建设科学技术奖一等奖1项、华为难题揭榜“火花奖”2项。
主要研究领域包括交通大数据分析与建模、交通网络规划与管理、公共交通、智能交通系统等。在Transportation Research Part B/Part C/Part E、Transportation Science、IEEE Transactions on Knowledge and Data Engineering（TKDE）、European Journal of Operational Research等知名期刊发表SCI/SSCI论文130余篇（皆为第一或通讯作者），论文被引用7300余次，其中ESI高被引论文10篇，自2021年起连续多年入选“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），担任交通研究领域知名SCI期刊Transportation Research Part E、ASCE Journal of Transportation Engineering、IEEE Intelligent Transport Systems Magazine、IET Intelligent Transport Systems副主编、Transportation Research Record（SCI）、Journal of Transport and Land Use（SSCI）编委，在多个学科领域的国际知名学术组织任职，包括人工智能学会智能交通分委会副主任、中国自动化学会综合智能交通专业委员会副主任、多模式交通运输国际研讨会执行主席等。
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（2020年）、与第二名（2019）年，及其他同为人工智能三大国际顶级赛事的IJCAI冠军（2019年）、NeurIPS第二名（2020年）。此外还包括，2016年阿里巴巴天池大赛算法挑战赛冠军、2016年首届滴滴算法大赛-亚军、2017年美国TRB大会数据分析比赛优秀论文奖、2017年CCF大数据与计算智能大赛亚军、2017年Ucar Artificial Intelligence Cup冠军(IEEE computer society)、2018年阿里巴巴天池大赛冠军、2019年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。
Dr. Zhiyuan (Terry) Liu is a Professor in the School of Transportation at Southeast University in Nanjing China. He attained his Ph.D degree from National University of Singapore (NUS) in Transportation Engineering in 2011. Prior to his studies in Singapore, he has obtained a Bachelor degree in Transportation Engineering from Southeast University. From 2011 to 2012, he worked as a postdoc research fellow in NUS. From 2012 to 2015, he was a lecturer in Monash University Australia, where he also served as the director of the Master of Transportation Systems Program. Any interested Ph.D applicants with a Master degree on Transportation Engineering or relevant areas are encouraged to apply for the international Ph.D program (with scholarship) in Southeast University at Nanjing China. If you have any queries, please email Dr. Liu for more information.
联系方式（Contact Info）：
Address：南京市江宁区东南大学路2号 31399金沙娱场城（211189）
Email：zhiyuanl@seu.edu.cn
主持纵向科研项目（Research Projects, as PI）：
1.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
2.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
3.多模式交通网络优化与管理（71922007），国家自然科学基金优秀青年基金，2020/01-2022/12
4.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
5.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
6.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
7.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
8.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
9.国家自然科学基金国际(地区)合作与交流项目（51561135003），低碳化进程中城市多模式交通系统运营关键问题研究--专题二，面向低碳运营的城市交通系统资源配置与智能优化，2015-2018
10.澳大利亚维州商务与创新局制造与生产基金子课题，模块化建筑单元的多模式运输，项目总额：120万澳币，2014-2017
Selected SCI/SSCI Papers (*corresponding author)：
2. 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.
3. 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.
4. Zhang, H., Liu, Z.*, Wang, J., Wu, Y., 2023. A Novel Flow Update Policy in Solving Traffic Assignment Problems: Successive Over Relaxation Iteration Method. Transportation Research Part E, 174, 103111.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. Liu, Y., Wu, F., Liu, Z., Wang, K., Wang, F., Qu, X.*, 2023. Can Language Models Be Used for Real-World Urban-Delivery Route Optimization? The Innovation, 4(6), 100520.
12. 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, 35, 12, 13043-13054.
13. Yin, R., Liu, X., Zheng, N., & Liu, Z.*., 2022. Simulation-based Analysis of Second-best Multimodal Network Capacity. Transportation Research Part C, 145, 103925.
14. 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.
15. 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.
16. 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.
17. Gu, Z., Wang, Z., Liu, Z., Saberi, M.*, 2022. Network Traffic Instability with Automated Driving and Cooperative Merging. Transportation Research Part C, 138, 103626.
18. Liu, Z.*, Wang, Y., Cheng, Q., and Yang, H., 2022. Analysis of the Information Entropy on Traffic Flows. IEEE Transactions on Intelligent Transportation Systems.
19. 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.
20. 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.
21. 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.
22. 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.
23. 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.
24. 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.
25. 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.
26. 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.
27. 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.
28. 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.
29. 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.
30. 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
31. 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.
32. Chen, X., Liu, Z.*, Kim, I., 2019. Parallel computing framework for solving user equilibrium problem on computer clusters. Transportmetrica A.
33. 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.
34. 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.
35. 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.
36. 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
37. 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
38. 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.
40. 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.
41. 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.
42. 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
43. 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.
44. 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.
45. 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.
46. 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.
47. 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.
48. 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.
49. 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.
50. 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.
51. 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.
52. 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.
53. 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
54. 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.
55. 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.
56. 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.
57. 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.
58. 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.
59. Wang, S.*, Liu, Z., Bell, M., 2015. Profit-based maritime container assignment models for liner shipping networks, Transportation Research Part B, 72, 59-76.
60. 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.
61. 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.
62. 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.
63. Wang, S., Liu, Z., Meng, Q.*, 2014. Segment-based alteration for container liner shipping network design, Transportation Research Part B, 72, 128-145.
64. 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.
65. 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.
66. 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.
67. Liu, Z., Meng, Q.*, Wang, S., Sun, Z., 2014. Global Intermodal Liner Shipping Network Design, Transportation Research Part E, 61, 28-39.
68. 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.
69. 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.
70. 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.
71. 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.
72. 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.
73. Wang, S., Meng, Q.*, and Liu, Z., 2013. Containership scheduling with transit-time-sensitive container shipment demand, Transportation Research Part B, 54, 68-83.
74. 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.
75. Meng, Q.*, Wang, S. and Liu, Z., 2012. Network Design for Shipping Service of Large-scale intermodal liners, Transportation Research Record, 2269, 42-50.
76. 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.
77. 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.
78. 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.
79. 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.
