Postdoctoral Fellow, Cornell University

Pengbo Zhu

My ambition is to bridge control theory and emerging urban transportation systems.

Portrait of Pengbo Zhu

I am currently a postdoctoral fellow working with Prof. Andreas A. Malikopoulos in the Information and Decision System Laboratory at Cornell University.

I received my Ph.D. from the Urban Transport Systems Laboratory at EPFL, co-supervised by Prof. Nikolas Geroliminis and Prof. Giancarlo Ferrari-Trecate. Before EPFL, I received my B.Sc. and M.Sc. degrees from Harbin Institute of Technology.

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Research

Control + Optimization for Mobility in the Future

My research lies at the intersection of control theory, optimization, and urban transportation systems, focusing on multi-agent systems, mobility-on-demand, and traffic control. I connect macroscopic traffic modeling with microscopic control and decision-making, developing methods for vehicle motion and path planning, cooperative drone operations, mixed-traffic routing, and data-driven control for next-generation mobility systems.

Selected Publications

Cooperative detour planning visualization

Cooperative Detour Planning for Dual-Task Drone Fleets [link]

Pengbo Zhu, Meng Xu, Andreas A. Malikopoulos, Nikolas Geroliminis

IEEE Conference on Decision and Control, 2026. Invited Session: Modeling and Control for Scalable Advanced Air Mobility Systems.

A decentralized framework for drone fleets that execute delivery tasks while observing traffic conditions. The method maximizes traffic information rewards under delivery detour and battery constraints.

Mixed traffic routing and intersection control diagram

Integrated Routing and Intersection Control for Mixed Traffic [link]

Filippos N. Tzortzoglou*, Pengbo Zhu*, Andreas A. Malikopoulos

IEEE Conference on Decision and Control, 2026.

A hierarchical framework that links network-level routing guidance for connected and automated vehicles with local signal phase and trajectory optimization at intersections.

Ride-pooling detour planning result

Detour Planning for Ride-Pooling Vehicles [link]

Pengbo Zhu, Giancarlo Ferrari-Trecate, Nikolas Geroliminis

European Control Conference, 2025. Invited Session: Novel Methods for Modeling and Control of Mobility and Traffic Systems.

A path-planning algorithm for partially occupied vehicles with available capacity, enabling immediate responses to passenger requests while coordinating demand-aware detours.

Data-enabled predictive control diagram

Model-Free Methods for Vehicle Rebalancing [link]

Pengbo Zhu, Giancarlo Ferrari-Trecate, Nikolas Geroliminis

IEEE Transactions on Control Systems Technology. Special Issue: Intelligent Decision Making, Planning, and Control of Automated Vehicles.

This paper constructs a multi-layer control structure to offer both inter-regional and intra-regional vehicle position guidance. We implement a novel data-enabled predictive control algorithm for inter-regional vehicle deployment to balance passenger demand and vehicle supply.

Approximate dynamic programming for vehicle rebalancing

Vehicle Rebalancing via Approximate Dynamic Programming [link]

Yunping Huang*, Pengbo Zhu*, Renxin Zhong, Nikolas Geroliminis

Transportation Research Part E: Logistics and Transportation Review.

A stochastic programming formulation solved with approximate dynamic programming to capture the dynamics of private and on-demand vehicles in mobility-on-demand systems.

Hierarchical vehicle repositioning framework

MFD Model-Based Vehicle Repositioning Method [link]

Caio Vitor Beojone, Pengbo Zhu, Isik Ilber Sirmatel, Nikolas Geroliminis

Transportation Research Part C: Emerging Technologies.

A Macroscopic Fundamental Diagram-based model and model predictive control method for inter-regional vehicle relocation, combined with lower-layer coverage control guidance.

Graph coverage control for vehicle rebalancing

A Coverage Control-Based Idle Vehicle Rebalancing Approach for Autonomous Mobility-on-Demand Systems [link]

Pengbo Zhu, Isik Ilber Sirmatel, Giancarlo Ferrari-Trecate, Nikolas Geroliminis

IEEE Transactions on Control Systems Technology.

An extension of coverage control for ride-sourcing systems to graph-structured urban road networks, improving practical implementation in city-scale settings.

Coverage control for ride-sourcing systems

Idle-Vehicle Rebalancing Coverage Control for Ride-Sourcing Systems [link]

Pengbo Zhu, Isik Ilber Sirmatel, Giancarlo Ferrari-Trecate, Nikolas Geroliminis

European Control Conference, 2022. London, United Kingdom.

A Voronoi-based coverage control formulation for proactively relocating idle vehicles toward high-demand districts in ride-sourcing systems.

Activities

EPFL My Thesis in 180 Seconds event

Finalist, EPFL My Thesis in 180 Seconds [link]

Finalist in the EPFL MT180 competition, presenting Ph.D. research to a broad audience in three minutes. The talk is available on the EPFL MT180 YouTube channel.

TRC 30 and MFTS 2024 conference

Organization Team, TRC 30 and MFTS 2024 [link]

Member of the organization team for the 30th anniversary of Transportation Research Part C, held with MFTS 2024 in Heraklion, Greece.

Urban transportation dataset

Open-Source Dataset for Urban Transportation Study [link]

Passenger request data for urban on-demand mobility in Shenzhen, associated with the ECC 2022 ride-sourcing coverage control paper.

NCCR Women campaign

NCCR Women Campaign [link]

A video introduction to my research on intelligent systems for ride-hailing vehicle distributions and the role of diversity in research.

NCCR Automation mobility of the future video

NCCR Automation: Developing the Mobility of the Future [link]

A video on how researchers address obstacles to make urban mobility more efficient.

Optimization and control summer school

Co-Organizer, Optimization and Control in Infrastructure Networks [link]

Co-organized an EPFL and ETH summer school on large-scale optimization and distributed control, with applications in power and transportation systems.

Teaching

Latest News

  1. I will give oral and poster presentations at the 3rd annual Northeast Systems and Control Workshop at Princeton University.
  2. I started my postdoctoral position at Cornell University in the IDS Lab.
  3. I successfully completed my public Ph.D. defense.
  4. I was awarded the Postdoc.Mobility Fellowship from the Swiss National Science Foundation.
  5. Our paper on detour planning for ride-pooling vehicles won the Best Paper Award at hEART 2025.
  6. Our paper was accepted to the 13th Symposium of the European Association for Research in Transportation.
  7. I joined the finalists of EPFL Final 2025.
  8. Our paper "En Route Path-Planning for Partially Occupied Vehicles in Ride-Pooling Systems" was accepted to the European Control Conference 2025.
  9. I presented recent work on detour planning at the EPFL ENAC internal seminar in Barcelona.
  10. I won first place in My Thesis in 180 Seconds at EDEE Scientific Day 2024.
  11. Our paper on bi-level vehicle relocation was published in Transportation Research Part E.
  12. I presented recent work during the EPFL ENAC Research Day poster exhibition.
  13. Our paper on hierarchical control for vehicle repositioning was published in IEEE Transactions on Control Systems Technology.
  14. I joined TRC 30 and MFTS 2024 in Heraklion, Greece, as part of the organization team.
  15. Our vehicle repositioning paper was presented at ISTTT 25 in Ann Arbor, Michigan.
  16. Our hierarchical control framework paper was published in Transportation Research Part C.
  17. Our coverage control paper was published in IEEE Transactions on Control Systems Technology.
  18. Our ITSC 2023 paper "A Two-Layer Approach for Rebalancing Ride-Hailing Vehicles" was published.
  19. I attended the IPAM workshop on mathematical foundations for equity in transportation systems at UCLA.
  20. I attended TRB 2024 and gave an oral presentation on model-free control for vehicle rebalancing.