Y. (Yongqiu) Zhu PhD
Y. (Yongqiu) Zhu PhD
Contact
Profile
Biography
Dr. Yongqiu Zhu is an Assistant Professor of multimodal transport network resilience at the Department of Transport and Planning. She addresses the challenges of uncertainty and scalability in (real-time) user-centric decision-making problems within passenger transport systems, leveraging reinforcement learning, data-driven approaches, optimization, simulation and heuristics. A particular focus is on public transport and its coordination with other emerging urban mobility, to withstand, respond, and adapt to the (unexpected) abnormal operational situations, including traffic disturbances, overcrowding, and disruptions.
In 2012, she earned her Master degree in in Traffic Transportation Planning and Management from Southwest Jiaotong University in China. Following a few months of visiting research at Erasmus University Rotterdam, she began her PhD study in 2016 at the Department of Transport and Planning at TU Delft. In December 2019, she successfully defended her PhD thesis, titled "Passenger-Oriented Timetable Rescheduling in Railway Disruption Management ", which was under the supervision of Prof. Rob M.P. Goverde. After completing her PhD, she worked as a postdoctoral researcher at TU Delft and TU Denmark, respectively. In these positions, she conducted research in new directions, focusing on resilient railways in extreme weather conditions (with NS and ProRail), reinforcement learning for real-time traffic management, and multimodal transportation. In December 2020, she was awarded the prestigious ETH Zurich Postdoctoral Fellowship, supporting her exploration of the potential of AI techniques in passenger-oriented traffic management and smart information provision. She conducted this research under the supervision of Prof. Francesco Corman at ETH Zurich in Switzerland from 2021 to 2023.
Yongqiu’s scientific contributions have received several awards, including the Best Paper Awards at the International Conference on Railway Operations Modelling and Analysis (ICROMA) in 2019 and 2021, the Young Operations Research Awards from the International Association of Railway Operations Research (IAROR) in 2019 and 2021, and the Best Presentation Award from the Transportation Research Board Annual Meeting in 2020.
Expertise
Publications
-
2024
Handling uncertainty in train timetable rescheduling
A review of the literature and future research directions
Shuguang Zhan / Jiemin Xie / S. C. Wong / Yongqiu Zhu / Francesco Corman -
2023
Bi-objective optimization of last-train timetabling with multimodal coordination in urban transportation
Jia Ning / Qiyuan Peng / Yongqiu Zhu / Xinjie Xing / Otto Anker Nielsen
-
2023
Reinforcement Learning in Railway Delay Management
Yongqiu Zhu / Pengling Wang / Francesco Corman
-
2023
Robust cooperative train trajectory optimization with stochastic delays under virtual coupling
Pengling Wang / Yongqiu Zhu / Wei Zhu
-
2023
Train traffic control in merging stations
A data-driven approach
Ping Huang / Zhongcan Li / Yongqiu Zhu / Chao Wen / Francesco Corman -
Courses 2024
Prizes
-
2020-1
Best Presentation Award in Doctoral Research Workshop of 2020 TRB Annual Meeting.
Best Presentation Award for presenting my PhD work "Passenger-Oriented Timetable Rescheduling in Railway Disruption Management" in Doctoral Research Workshop of Transportation Modelling and Travel Behavior at 2020 TRB Annual Meeting.
Transportation Research Board (TRB) 99th Annual Meeting -
2019-7
The 2nd Best Paper in the 8th International Conference on Railway Operations Modelling and Analysis (RailNorrköping 2019)
-
2019-6
Young Railway Operations Research Award 2019
3rd prize to Yongqiu Zhu (Delft University of Technology) for her excellent and innovative paper ‘Dynamic and robust timetable rescheduling for uncertain railway disruptions’
Ancillary activities
-
2023-08-01 - 2025-01-31