MOVE LabMobility Optimization for Value and Efficiency
Dr. Fangni Zhang
Associate Professor
Department of Data and Systems Engineering, The University of Hong Kong
Deputy Director
Institute of Transport Studies, The University of Hong Kong
Summary
Dr. Fangni Zhang is an Associate Professor in the Department of Data and Systems Engineering at The University of Hong Kong. She holds a B.S. in Industrial Engineering from Beihang University and a Ph.D. in Transportation Engineering from The Hong Kong University of Science and Technology. Dr. Zhang’s research focuses on transportation economics, analytics, and optimization, with an emphasis on automated, shared, and multimodal mobility systems. Her work addresses critical challenges in planning, operations, and management to advance sustainable and intelligent transportation systems. Her research has been funded by competitive grants from the Hong Kong Research Grants Council (RGC) and the National Natural Science Foundation of China (NSFC).
Research interests
Low-altitude logistics systems optimization
We investigate low-altitude logistics network design and operational optimization, focusing on drone–ground coordination, infrastructure planning, and routing under uncertainty to enhance system efficiency, reliability, and resilience within practical operational constraints.
Mobility and logistics network modeling
We model mobility and logistics networks to examine interactions among travelers, operators, and infrastructure, integrating network optimization and equilibrium analysis to inform system planning, pricing, and resource allocation across modes.
Autonomous vehicle/UAV systems operations
We study operational strategies for autonomous vehicle and UAV systems, addressing fleet management, task allocation, and coordinated routing to improve service performance under demand variability, travel uncertainty, and resource constraints.
AI for transportation
We develop machine learning methods for transportation forecasting and decision support, integrating spatiotemporal modeling with optimization to characterize mobility patterns, predict network conditions, and support adaptive planning and operational decisions.
PhD, Postdoc & Research Assistant positions
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I am looking for 1-2 self-motivated Ph.D. students to join my research group. Applicants should have a B.S. or M.S. in Transportation Engineering, Data Science, Computer Science, Automation, and Applied Mathematics, or related fields. Strong oral and written communication skills in English are required. Candidates with research experience in network modeling, optimization and game theory are preferred.
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Successful applicants will be considered eligible to receive a Postgraduate Scholarship (the 2025 rate: HK$19,135/month in probation and HK$19,655/month after probation) during the normative study period. Outstanding applicants for the Ph.D. programme are strongly encouraged to apply for the Hong Kong PhD Fellowship (HKPF) scheme, which offers an annual stipend of HK$28,400/month plus a conference and research-related travel allowance of HK$14,400/year. HKU will provide HKPF awardees additional living allowance (HK$20-40k/year) and accommodation support. To learn more about the HKU Ph.D. programme and scholarships, visit HKU Graduate School website.
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Postdoc, Research Assistant, and visiting research positions are also available. If your research background fits my research interests, please send me your CV including your education qualifications and list of publications.
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Please contact Dr. Fangni Zhang directly at fnzhang.at.hku.hk
Selected Publications
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Li, Q., Zhang, F. (2026) Auction mechanism design for order allocation and payment in a crowdshipping system. Transportation Science, DOI: 10.1287/trsc.2025.0089.
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Sun, W., Wu, L., Zhang, F. (2026) An Exact Algorithm to Solve Vehicle Routing Problem with Drones for Delivery and Surveillance Tasks After Disasters. Transportation Science, 60(1), 132-154.
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Sun, W., Wu, L., Zhang, F. (2026) Robust optimization for truck-and-drone collaboration with travel time uncertainties. Transportation Research Part B: Methodological, 204, 103378.
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Lin, J., Zhang, F., Yin, Y. (2026) Parking-and-Charging-as-a-Service: Online admission and allocation policies for an integrated parking and charging reservation system. Transportation Research Part B: Methodological, 204, 103375.
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Zhang, Z., Zhang, F., Liu, W. (2025) To park or to share your autonomous vehicle?. Transportation Research Part B: Methodological, 200, 103305.
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Zhang, Z., Zhang, F., Liu, W. (2025) Economic analysis of parking, vehicle charging and vehicle-to-grid service in the era of electric vehicles. Transportation Research Part B: Methodological, 191, 103133.
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Zhang, Z., Zhang, F. (2024) Optimal operation strategies of an urban crowdshipping platform in asset-light, asset-medium, or asset-heavy business format. Transportation Research Part B: Methodological, 102992.
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Gong, Z., Zhang, F., Liu, W., Graham, D. (2023) On the effects of airport capacity expansion under responsive airlines and elastic passenger demand. Transportation Research Part B: Methodological, 170, 48-76.
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Zhang, F., Lindsey, R., Yang, H., Shao, C., Liu, W. (2022) Two-sided pricing strategies for a parking sharing platform: reselling or commissioning? Transportation Research Part B: Methodological, 163, 40-63.
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Liu, W., Zhang, F., Wang, X., Shao, C., Yang, H. (2022) Unlock the sharing economy: the case of the parking sector for recurrent commuting trips. Transportation Science, 56(2), 265-564.
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Ma, M., Zhang, F., Liu, W., Dixit, V. (2022) A game theoretical analysis of metro-integrated city logistics systems. Transportation Research Part B: Methodological, 156, 14-27.
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Liu, W., Zhang, F., Yang, H. (2017) Modeling and managing morning commute with both household and individual travels. Transportation Research Part B: Methodological, 103, 227-247.
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Zhang, F., Lindsey, R. and Yang, H. (2016) The Downs–Thomson paradox with imperfect mode substitutes and alternative transit administration regimes. Transportation Research Part B: Methodological, 86, 104-127.