Dr. Fang He is a tenured Associate Professor and Ph.D. supervisor in the Department of Industrial Engineering at Tsinghua University, where he currently serves as the Deputy Director of Research. Dr. He was selected as a Young Top-notch Talent under the “Ten Thousand Talents Program” by the Organization Department of the CPC Central Committee.

Dr. He has long been dedicated to teaching and research in the field of transportation operations and management. His research interests include:

Methodologies:

• Network Modeling and Optimization

• Large-scale Combinatorial Optimization

• Deep Learning & Deep Reinforcement Learning

Application Domains:

• Ride-sourcing

• Maritime Logistics

• Logistics & Warehousing

• Electric Vehicle Charging & Battery Swapping Infrastructure

Dr. He’s research group regularly recruits Ph.D. students and welcomes applications from students with strong academic interests. The group also seeks qualified postdoctoral fellows and contract researchers.

Laboratory WeChat Official Account: THU-STORM

• Ph.D. in Department of Civil and Coastal Engineering, University of Florida, USA, 2010 – 2014, Advisor: Prof. Yafeng Yin

• B.S. in Department of Civil Engineering, Tsinghua University, 2006 – 2010

Academic Positions

• Tenured Associate Professor, Department of Industrial Engineering, Tsinghua University, Jul. 2020 – Present

• Associate Professor, Department of Industrial Engineering, Tsinghua University, Dec. 2016 – Jun. 2020

• Assistant Professor, Department of Industrial Engineering, Tsinghua University, Oct. 2014 – Dec. 2016

Administrative Roles

• Deputy Director of Research, Department of Industrial Engineering, Tsinghua University, Jan. 2024 – Present

• Deputy Party Secretary, Department of Industrial Engineering, Tsinghua University, Mar. 2021 – Apr. 2024

• Head of Graduate Affairs Committee, Department of Industrial Engineering, Tsinghua University, Jul. 2017 – Jan. 2021

• Young Top-notch Talent, National “Ten Thousand Talents Program”, Organization Department of the CPC Central Committee, 2020

• Rated “Outstanding” (Top Grade) in Project Evaluation, National Natural Science Foundation of China (General Program, PI), 2025

• Second Prize, Science and Technology Progress Award, China Highway and Transportation Society (First Recipient, First Affiliated Institution), 2024

• Elsevier Highly Cited Chinese Researcher, 2019–2024

• Lin Feng Counselor Award (as faculty), Tsinghua University, 2023

• Top Paper Award in the theme “Integrated Development of Power and Transportation Networks”, Automation of Electric Power Systems, 2023

• Panel Expert, NSFC Railway Basic Research Joint Fund (Management Division), 2022

• Outstanding Doctoral Dissertation Advisor, Tsinghua University, 2022

• Outstanding Master’s Thesis Advisor, Tsinghua University, 2022

• Outstanding Undergraduate Thesis Advisor, Beijing Municipal Education Commission, 2021

• Excellence Award for Online Teaching during COVID-19, Tsinghua University, 2020

• First Prize for Excellence in Student Research Training (SRT) Program Advising, Tsinghua University, 2019

• Best Paper Award, 11th International Conference on Computational Transportation Science (ICTS), 2019

• Comprehensive Excellence Award, Department of Industrial Engineering, Tsinghua University, 2015, 2016, 2019

• Research Excellence Award, Department of Industrial Engineering, Tsinghua University, 2016–2019

• Teaching Excellence Award, Department of Industrial Engineering, Tsinghua University, 2016, 2018, 2019

• Best Paper Award, 18th COTA International Conference of Transportation Professionals (CICTP), 2018

• Stella Dafermos Best Paper Nomination, TRB Committee on Network Modeling (ADB30), U.S. Transportation Research Board, 2015

• Outstanding Academic Achievement Award, School of Sustainable Engineering, University of Florida, 2014

Google Scholar Citation=5414, H-index=32, as of 2025.6.23

Referred Journals:

1. Du, C., He, F.*, & Lin, X. (2025). Dynamic pricing for air cargo revenue management. Transportation Research Part E: Logistics and Transportation Review, 197, 104088.

2. Gao, C., Wang, Y., He, F.*, & Lin, X. (2025). Modeling and analyzing ride-hailing market equilibrium considering drivers’ multi-homing choice behavior. Transportation Research Part E: Logistics and Transportation Review, 197, 104055.

3. Yang, J., He, F.*, Shen, Z.J., Lin, X. (2024). Dynamic pricing and service fulfillment of mobile charging systems with stochastic demands. Production and Operations Management.

4. Yan, Y., Lin, X., He, F., & Wang, D. Z.* (2024). Dynamic Operations of a Mobile Charging Crowdsourcing Platform. Transportation Science, 58(5), 995-1015.

5. Lin, X., Chen, Z.*, Li, M., & He, F. (2024). Bunching-Proof Capabilities of Modular Buses: An Analytical Assessment. Transportation Science.

6. Dai, H., He, F.*, & Lin, X. (2024). Integrated operations strategies for shared and privately-owned autonomous vehicles: A deep reinforcement learning framework. Transportation Research Part C: Emerging Technologies, 163, 104621.

7. Si, J., He, F.*, Lin, X., & Tang, X. (2024). Vehicle dispatching and routing of on-demand intercity ride-pooling services: A multi-agent hierarchical reinforcement learning approach. Transportation Research Part E: Logistics and Transportation Review, 186, 103551.

8. Gao, C., Lin, X., He, F.*, & Tang, X. (2024). Online relocating and matching of ride-hailing services: A model-based modular approach. Transportation Research Part E: Logistics and Transportation Review, 188, 103600.

9. Tang, X., Yang, J., Lin, X., He, F.*, & Si, J. (2023). Dynamic operations of an integrated mobility service system of fixed-route transits and flexible electric buses. Transportation Research Part E: Logistics and Transportation Review, 173, 103081.

10. Chen, X., Lin, X., Li, M.*, He, F., & Meng, Q. (2023). A nearly throughput-maximum knotted intersection design and control for connected and automated vehicles. Transportation research part B: methodological, 171, 44-79.

11. Liu, Q., Lin, X., Li, M.*, Li, L., & He, F. (2023). Coordinated lane-changing scheduling of multilane CAV platoons in heterogeneous scenarios. Transportation Research Part C: Emerging Technologies, 147, 103992.

12. Yang, C., Lin, X., Li, M.*, & He, F. (2022). Simulation Comparisons of Vehicle-Based and Movement-Based Traffic Control for Autonomous Vehicles at Isolated Intersections. IEEE Transactions on Intelligent Transportation Systems, 23(12), 22954-22970.

13. Wang, Y., Lin, X., He, F.*, & Li, M. (2022). Designing transit-oriented multi-modal transportation systems considering travelers’ choices. Transportation Research Part B: Methodological, 162, 292-327.

14. Chen, X., Lin, X., Li, M.*, & He, F. (2022). Network-level control of heterogeneous automated traffic guaranteeing bus priority. Transportation Research Part C: Emerging Technologies, 140, 103671.

15. Chen, X., Lin, X., Li, M.*, & He, F. (2022). Multi-rhythm control for heterogeneous traffic and road networks in CAV environments. Transportation Research Part E: Logistics and Transportation Review, 160, 102672.

16. Li, M.*, Tang, P., Lin, X., & He, F. (2022). Multistage planning of electric transit charging facilities under build-operate-transfer model. and Environment, 102, 103118.Transportation Research Part D: Transport

17. Yang, J., He, F.*, Lin, X., Shen, Z.J.*, 2021. Mechanism Design for Stochastic Dynamic Parking Resource Allocation. 30(1), 23–42. Production and Operations Management,

18. Chen, Xiangdong; Li, Meng; Lin, Xi; Yin, Yafeng; HE, FANG*. Rhythmic Control of Automated Traffic-Part I: Concept and Properties at Isolated Intersections. 55(5), 1233–1256. Transportation Science,

19. Lin, X., Li, M., Shen, Z.-J., Yin, Y., He, F.*, 2021. Rhythmic Control of Automated Traffic Part II: Grid Network Rhythm and Online Routing. 55(5), 1257–1279. Transportation Science.

20. An, Y., Lin, X., Li, M.*, He, F., 2021. Dynamic Governance Decisions on Multi-modal Inter-city Travel during a Large-scale Epidemic Spreading. 110, 38–49.Transport Policy.

21. Huang, K., Wu, J.*, Liao, F.*, Sun, H., He, F., Gao, Z., 2020. Incorporating multimodal coordination into timetabling optimization of the last trains in an urban railway network. 114, 64–86.Transportation Research Part C: Emerging Technologies.

22. Zhang, Z., He, F., Lin, X., Wang, Y., Li, M.*, 2020. High-performance traffic speed forecasting based on spatiotemporal clustering of road segments. 14(8), 938–944.IET Intelligent Transport Systems.

23. Wang, Y., Li, M., Lin, X., He, F.*, 2020. Online operations strategies for automated multistory parking facilities. 139, 101956.Transportation Research Part E: Logistics and Transportation Review.

24. Chengzhang Wang, Fang He, Xi Lin, Max Zuo-Jun Shen and Meng Li*，2020. Hybrid of Fixed and Mobile Charging Systems for Electric Vehicles: System Design and Analysis. Accepted in ISTTT24 Symposium, Published in Special Issue of Transportation Research Part C: Emerging Technologies, 115, 102622.

25. Tang, X., Li, M., Lin, X., He, F.*, 2020. Online operations of automated electric taxi fleets: a two-step reinforcement learning framework. 115, 102621.Transportation Research Part C: Emerging Technologies.

26. Chen, X., Lin, X., He, F., Li, M., 2020. Modeling and Control of Automated Vehicle Access on Dedicated Bus Rapid Transit Lanes. 115, 102607.Transportation Research Part C: Emerging Technologies.

27. Zhang, K., He, F., Zhang, Z., Lin, X., Li, M.*, 2020. Data-driven traffic speed forecasting: graph attention temporal convolutional network. Transportmetrica B: Transport Dynamics, 8(1), 375–395.

28. Tang, P., He, F., Lin, X., Li, M.*, 2020. Online-to-offline mobile charging system for electric vehicles: strategic planning and online operation. 87, 102518.Transportation Research Part D: Transport and Environment.

29. Zhang, K., He, F., Zhang, Z., Lin, X., Li, M.*, 2020. Multi-vehicle routing problems with soft time windows: a multi-agent reinforcement learning approach. 121, 102861.Transportation Research Part C: Emerging Technologies.

30. An, Y., Li, M., Lin, X., He, F.*, Yang, H., 2020. Conflict-free routing in dedicated automated vehicle zones. 120, 102777.Transportation Research Part C: Emerging Technologies.

31. Li, H., Li, M., Lin, X., He, F.*, Wang, Y., 2020 Traffic data imputation with complicated missing patterns: a combined approach with prophet time series and iterative random forest. 119, 102730.Transportation Research Part C: Emerging Technologies.

32. Lin, X., Yin, Y., He, F.*, 2020. Credit-based mobility management considering travelers' budgeting behaviors under uncertainty. 55(2), 297–314.Transportation Science.

33. Luo Z., He F., Lin, X., Wu, J., Li, M.*, 2020. Joint deployment of charging stations and photovoltaic power plants for electric vehicles. 79, 102247.Transportation Research Part D: Transport and Environment.

34. Lin, X., He, F.*, Li, M., Liu, Y., 2019. On the existence of system-optimum-inducing tolling functions for transportation networks. 54(6), 1535–1554.Transportation Science.

35. Yan, H., He, F., Lin, X., Yu, J., Li, M.* and Wang, Y., 2019. Network-level multiband signal coordination scheme based on vehicle trajectory data. Transportation Research Part C: Emerging Technologies, 107, pp.266-286.

36. Tang, X., Lin, X. and He, F.*, 2019. Robust scheduling strategies of electric buses under stochastic traffic conditions. Transportation Research Part C: Emerging Technologies, 105, pp.163-182.

37. Zhang, Z., Li, M., Lin, X., Wang, Y. and He, F.*, 2019. Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies. Transportation Research Part C: Emerging Technologies, 105, pp.297-322.

38. Wang, C., He, F., Lin, X., Shen, Z.J.M. and Li, M.*, 2019. Designing locations and capacities for charging stations to support intercity travel of electric vehicles: An expanded network approach. Transportation Research Part C: Emerging Technologies, 102, pp.210-232.

39. Li, H., He, F., Lin, X., Wang, Y. and Li, M.*, 2019. Travel time reliability measure based on predictability using the Lempel–Ziv algorithm. Transportation Research Part C: Emerging Technologies, 101, pp.161-180.

40. Yang, Y.*, Li, M., Yu, J. and He, F., 2019. Expressway bottleneck pattern identification using traffic big data—The case of ring roads in Beijing, China. Journal of Intelligent Transportation Systems, pp.1-14.

41. He, F., Yang, J., and Li, M.*, 2018. Vehicle scheduling under stochastic trip times: An approximate dynamic programming approach. Transportation Research Part C: Emerging Technologies, 96, 144-159.

42. Lin, X., Li, M., and He, F*., 2018. Nonlinear pricing in linear cities with elastic demands. Transportation Research Part C: Emerging Technologies, 95, 616-635.

43. He, F*., Wang, X., Lin, X. and Tang, X., 2018. Pricing and penalty/compensation strategies of a taxi-hailing platform. Transportation Research Part C: Emerging Technologies, 86, pp.263-279.

44. Chen, Z., He, F., and Yin, Y.*, 2017. Optimal design of autonomous vehicle zones in transportation networks. Transportation Research Part B. Vol. 99, 44-61.

45. Kontou, E.*, Yin, Y., Lin, Z., He, F., 2017. Socially optimal replacement of conventional with electric vehicles for the US household fleet. International Journal of Sustainable Transportation, 11(10), 749-763.

46. Li, M., Jia, Y., Shen, Z.M., He, F.*, 2017. Improving the electrification rate of the vehicle miles traveled in Beijing: A data-driven approach. Transportation Research Part A. Vol. 97, 106-120.

47. Chen, Z., He, F., Zhang L.* and Yin Y., 2016. Optimal deployment of autonomous vehicle lanes with endogenous market penetration. Transportation Research Part C. Vol. 72, 143-156.

48. Wang, X.*, He, F., Yang, H. and Gao, H.O., 2016. Pricing strategies for a taxi-hailing platform. Transportation Research Part E. Vol. 93, 212-231.

49. Chen, Z., He, F. and Yin, Y.*, 2016. Optimal deployment of charging lanes in transportation networks. Transportation Research Part B. Vol. 91, 344-365.

50. Li, M., Lin, X., He, F.* and Jiang, H., 2016. Optimal locations and travel time display for variable message signs. Transportation Research Part C. Vol. 69, 418-435.

51. He, F., Yin, Y.*, Wang, J., and Yang, Y., 2016. Optimal prices of electricity at public charging stations for plug-in electric vehicles. Networks and Spatial Economics. Vol. 16, 131-154.

52. He, F.*, and Yin, Y., 2015. Deploying public charging stations on urban road networks. Transportation Research Part C. Vol. 60, 227-240.

53. He, F.* and Shen, Z.M., 2015. Modeling taxi services with smartphone-based e-hailing applications. Transportation Research Part C. Vol. 58, 93-106.

54. He, F., Yin, Y.*, Chen, Z., and Zhou, J., 2015. Pricing of parking games with atomic players. Transportation Research Part B. Vol. 73, 1-12.

55. Chen, Z., Yin, Y.*, He, F. and Lin, J.L., 2015. Parking reservation for managing downtown curbside parking. Transportation Research Record. Vol. 2498, 12-18.

56. He, F., Yin, Y.*, and Lawphongpanich, S., 2014. Network equilibrium models with battery electric vehicles. Transportation Research Part B. Vol. 67, 306-319.

57. He, F., Yin, Y.*, Nima, S., and Nie, Y., 2013. Tradable credit schemes on networks with mixed equilibrium behaviors. Transportation Research Part B. Vol. 57, 47-65.

58. He, F., Yin, Y.*, and Zhou, J., 2013. Integrated pricing of roads and electricity enabled by wireless power transfer. Transportation Research Part C. Vol. 34, 1-15.

59. He, F., Wu, D., Yin, Y.*, and Guan, Y., 2013. Optimal deployment of public charging stations for plug-in hybrid electric vehicles. Transportation Research Part B. Vol. 47, 87-101.

Government-Funded Projects

• Game Theory and Aggregation in Multi-Platform Ride-Hailing Markets: Equilibrium Analysis and Operational Strategy Optimization, General Program, National Natural Science Foundation of China (NSFC), Principal Investigator

• Key Issues in Urban Traffic Management Considering Vehicle Intelligence and Connectivity, Young Top-notch Talent Program, Organization Department of the CPC Central Committee, Principal Investigator

• Application Boundaries and Coordinated Regulation Models for Emerging Transportation Modes, Key Project, National Key R&D Program of China, Principal Investigator

• Planning and Operational Theories for Urban Transportation Electrification, General Program, NSFC, Principal Investigator (rated “Outstanding” in final evaluation)

• Public Charging and Battery Swapping Infrastructure Planning Based on Chain-based Travel Behavior, Youth Program, NSFC, Principal Investigator

• Urban Taxi Network Equilibrium Modeling and Operational Optimization with E-Hailing Platforms, Beijing Natural Science Foundation, Principal Investigator

• Innovative Models of Transport Governance and Service in the Era of Big Data, Ministry of Transport of the People’s Republic of China, Co-Principal Investigator

• Planning and Operational Technologies for the Integration of Energy, Information, and Transportation Networks, Key Project under NSFC Joint Fund, Co-Principal Investigator

Industry-Sponsored Projects

• Beijing Bailongma Yunxing Technology Co., Ltd.

• Big Data-Driven Smart Marketing Algorithms for Ride-Hailing Platforms, Principal Investigator

• Hubei Rongchuang Technology Co., Ltd.

• Big Data Analysis and Mining of Public Charging Behavior in Wuhan (2023), Principal Investigator

• Ningbo Zhoushan Port Co., Ltd.

• Smart Scheduling Algorithm for Shulanghu Terminal Operations, Subproject Leader

• Toyota Motor Corporation

• Smart Mobility Systems and Demonstration for Smart Cities (Toyota Interdisciplinary Initiative, 2022), Subproject Leader

• Design and Operational Optimization of Multi-Modal Urban Public Mobility Systems, Principal Investigator

• Efficiency Enhancement of Urban Multi-Modal Transportation Systems under Autonomous Driving, Principal Investigator

• Data-Driven Research on Optimal Pricing Strategies to Alleviate Urban Congestion, Principal Investigator

• Network Flow Control Methods Based on Rhythmic Theory, Principal Investigator

• Toyota Preliminary Research Initiative

• Data-Driven Research on Congestion Pricing Strategies, Principal Investigator

• Daimler AG (Mercedes-Benz)

• Development of General Evaluation Criteria for Autonomous Driving Assistance Systems, Subproject Leader

• Multi-Modal Transportation Big Data Analysis, Principal Investigator

• Amap (AutoNavi Software Co., Ltd.)

• Traffic Big Data Analysis and Application, Subproject Leader

• Traffic Condition Forecasting, Subproject Leader

• Correlation Analysis between Traffic and Pollutant Emissions, Subproject Leader

• Policy Research on Alleviating Traffic Congestion Based on Big Data Analytics, Subproject Leader

• Multi-Modal Traffic Big Data Analysis and Congestion Management under Oversaturated Conditions, Principal Investigator

• Traffic Big Data Mining and Information Analytics, Principal Investigator

• Shanghai Relic Fitness Equipment Co., Ltd.

• Sales Forecasting Based on Machine Learning Models, Principal Investigator

• China Academy of Civil Aviation Science and Technology

• Development of Flight Monitoring Systems, Subproject Leader

• Associate Editor, Transportation Science , 2025–present

• Editorial Board Editor, Transportation Research Part B: Methodological, 2021–present

• Editor, Transportation Research Part C: Emerging Technologies, 2017–present

• Executive Council Member, Transportation Management Subcommittee, Chinese Society of Management Science and Engineering, 2017–present

• Contributing Correspondent, Frontiers of Engineering Management, Journal of the Chinese Academy of Engineering, 2022–present

• Review Panelist, Railway Joint Research Fund, National Natural Science Foundation of China (NSFC), 2022

• Standing Council Member, Higher Education Management Subcommittee, China Society of Dialectics of Nature, 2020–2021

• Executive Council Member, Electric Vehicle Technology Committee, IEEE PES China Chapter, 2020–2021

• Guest Editor, Special Issue on Integrated Development of Grid and Transportation Networks, Journal of Transportation Engineering, 2020–2021

• Guest Editor, Special Issue on Smart Grid, IET Smart Grid, 2019–2020

• Ad-hoc Reviewer, National Natural Science Foundation of China, 2018–2020

• Committee Member, Technical Committee on Transportation Network Design, World Transport Convention, 2018

• Expert Consultant, Expert Database of Beijing Traffic Management Bureau, 2019–present

• Executive Committee Member, Tsinghua-Daimler Sustainable Transportation Research Center, 2016–2019

• Program Director, Joint Program on Artificial Intelligence Innovation and Entrepreneurship, Tsinghua University, 2017–2020

• Committee Member, Tsinghua University Center for Future Transportation and Smart Vehicles, 2018–2021

• Keynote Speech, AI Driving Innovation in Digital Supply Chain Services, Global Port and Shipping Partnership Conference, Ocean Alliance, 2025

• Session Chair, Sub-forum on Transportation Electrification, INFORMS Annual Meeting, 2025

• Organizing Committee Member, 25th International Symposium on Transportation and Traffic Theory (ISTTT), 2023

• Invited Talk, High-level Administrative Forum, 29th ITS World Congress, 2023

• Track Program Committee Member, Winter Simulation Conference (WSC), 2024

• Facility Planning and Operations Management for Electric Vehicles, 4th IEEE Conference on Energy Internet and Energy System Integration, 2020

• Optimizing Urban Transportation Organization in the Era of Autonomous Driving, 3rd Young Scholars Forum on Transportation Engineering and Management, 2020

• Towards Future Mobility: Opportunities, Challenges, and Paths, Annual Meeting of the Network Optimization Subcommittee, Operations Research Society of China, 2020

• Towards Future Mobility: Opportunities, Challenges, and Paths, International Workshop on Optimization Challenges and Opportunities in Logistics and Mobility, Beijing, 2019

• A Rhythmic Control Framework for Connected and Automated Vehicles on One-Way Grid Networks, Workshop on Ride-Sourcing Systems and Data-Driven Transportation Management, Nanjing, 2019

• Rhythmic Control of Automated Vehicles for Isolated Intersections, Workshop for Young Scholars of Transportation Engineering and Management, Nanjing, 2019

• Credit-based Mobility Management Considering Travelers’ Budgeting Behavior under Uncertainty, International Workshop on Multi-Modal Transportation, Beijing, 2019

• Infrastructure-Based Cloud Control of Automated Transportation, IEEE International ITS Conference, Hawaii, 2018

• The Date That Can’t Be Late – Traffic Status Forecasting Based on Deep Learning, The Computing Conference (Yunqi), Hangzhou, 2018

• Multi-source Big Data Driven Transportation Management Decision and Optimization, 2018 Smart China Expo, Transportation Forum, Chongqing, 2018

• Vehicle Scheduling under Stochastic Trip Times: An Approximate Dynamic Programming Approach, Alumni Forum, Department of Civil Engineering, Tsinghua University, 2018

• Vehicle Scheduling under Stochastic Trip Times: An Approximate Dynamic Programming Approach, World Transport Convention (WTC), Traffic Network Modeling Session, Beijing, 2018

• Big Data Driven Transportation Management, Beijing Carsmart Technology Co., Ltd., 2017

• A Systematic Investigation of General Nonlinear Road Pricing, University of Michigan, Ann Arbor, USA (Seminar), 2017

• Optimal Design of Urban Taxi Fleet Electrification: A Simulation-Based Optimization Approach, INFORMS Annual Meeting, Houston, USA (Invited Presentation), 2017

• Vehicle Scheduling under Stochastic Trip Times: An Approximate Dynamic Programming Approach, University of Michigan, Ann Arbor, USA (Seminar), 2017

• A Systematic Investigation of General Nonlinear Road Pricing, Beihang University, Beijing Jiaotong University, and Shanghai Jiaotong University (Seminar), 2017

• Improving the Electrification Rate of Vehicle Miles Traveled in Beijing: A Data-Driven Approach, NSFC Conference for Young Scholars – Management Science and Engineering, Anhui Polytechnic University, 2016