Academic Staff

PhD (Cranfield); PhD (NUAA); BEng (NUAA)

Areas of Specialisation

• Artificial Intelligence for Air Traffic Management
• Human–AI Collaboration in Air Traffic Management
• Advanced Concepts and Architectures for Future Air Traffic Management
  
  

Prof. Yutong Chen is an Assistant Professor in the Department of Aeronautical and Aviation Engineering at The Hong Kong Polytechnic University. He received his PhD degree in Aerospace Engineering from Cranfield University, United Kingdom, and a PhD degree in Transportation Engineering from Nanjing University of Aeronautics and Astronautics, China (awarded independently). Prior to joining PolyU, he was a Postdoctoral Research Fellow at the Air Traffic Management Research Institute (ATMRI), Nanyang Technological University, Singapore, where he was involved in and led several large-scale international air traffic management research projects funded by the European Union SESAR programme and the Civil Aviation Authority of Singapore (CAAS).

Prof. Chen’s research lies at the intersection of artificial intelligence, human–AI collaboration, and Air Traffic Management (ATM). His research has established a solid foundation in AI-enabled and human-centred decision support methods for air traffic management. His work has been applied to air traffic flow and capacity management, trajectory optimisation, and conflict management, with particular emphasis on human-in-the-loop system design, explainability, and deployability in safety-critical aviation environments. Related methods and concepts have also been extended to Unmanned Aircraft System Traffic Management (UTM) scenarios.

Prof. Chen has received several international recognitions for his research contributions. He is the Winner of the SESAR Young Scientist Award and has been inducted into the SESAR Young Scientist Hall of Fame. He also received the Second Prize of the Europe Air Transport Innovation Network, organised by EUROCONTROL. In addition, projects to which he contributed have been recognised with the SESAR Digital European Sky Awards – Exploratory Research Award. His research has been published in leading journals in transportation and aerospace engineering and validated in multiple international research programmes.

At PolyU, Prof. Chen continues his research on intelligent and human-centred air traffic management systems, focusing on AI-enabled decision support, traffic prediction, system analysis, capacity assessment, and policy-relevant evaluation, with the aim of supporting the development of safe, efficient, and sustainable aviation operations in Hong Kong and the wider region.

Recruitment
Prof. Chen is currently recruiting PhD students (with opportunities for full scholarships), postdoctoral research fellows, and research assistants. Research topics include Air Traffic Management, Artificial Intelligence, and Human–AI Collaboration, with an emphasis on intelligent and human-centred aviation systems.

Applicants with a background in civil aviation, air traffic management, aerospace or transportation engineering, as well as those with strong training or research experience in artificial intelligence or human–AI teaming, are encouraged to apply. Relevant industry or operational experience in aviation is considered an advantage.

Interested candidates are welcome to contact Prof. Chen at yutong-cyt.chen@polyu.edu.hk, enclosing a CV and a brief statement of research interests.

Representative Publications in Last Five Years

1. Chen Y, Xu Y, Yang L, et al. Pre-Flight Fast Hotspot-Free and Conflict-Free Trajectory Planning for On-Demand UAV Delivery Logistics. Transportation Research Part E: Logistics and Transportation Review, 2026, 206: 104539.
   
   
2. Chen Y, Dalmau R, Alam S. Tactical Demand and Capacity Balancing Using Incremental Search in Spatio-Temporal Graphs with Flight Uncertainty. Transportation Research Part C: Emerging Technologies, 2025, 181: 105382.
   
   
3. Chen Y, Xu Y, Yang L, et al. In-Flight Fast Conflict-Free Trajectory Re-Planning Considering UAV Position Uncertainty and Energy Consumption. Transportation Research Part C: Emerging Technologies, 2025, 171: 104988.
   
   
4. Chen Y, Xu Y, Yang L, et al. A General Real-Time Three-Dimensional Multi-Aircraft Conflict Resolution Method Using Multi-Agent Reinforcement Learning. Transportation Research Part C: Emerging Technologies, 2023, 157: 104367.
   
   
5. Chen Y, Xu Y, Hu M. General Multi-Agent Reinforcement Learning Integrating Heuristic-Based Delay Priority Strategy for Demand and Capacity Balancing. Transportation Research Part C: Emerging Technologies, 2023, 153: 104218.
   
   
6. Chen Y, Hu M, Yang L, et al. General Multi-Agent Reinforcement Learning Integrating Adaptive Manoeuvre Strategy for Real-Time Multi-Aircraft Conflict Resolution. Transportation Research Part C: Emerging Technologies, 2023, 151: 104125.
   
   
7. Chen Y, Hu M, Xu Y, et al. Locally Generalised Multi-Agent Reinforcement Learning for Demand and Capacity Balancing with Customised Neural Networks. Chinese Journal of Aeronautics, 2023, 36(4): 338-353.
   
   
8. Chen Y, Hu M, Yang L. Autonomous Planning of Optimal Four-Dimensional Trajectory for Real-time En-Route Airspace Operation with Solution Space Visualisation. Transportation Research Part C: Emerging Technologies, 2022, 140: 103701.