Tianyu Zhao
Research Associate, Imperial
Air traffic demand and capacity balancing in the presence of disruptions
Research
Tianyu’s thesis developed national-scale simulation and rolling-horizon optimisation methods for air traffic demand and capacity balancing under disruptions such as severe weather, including resilience metrics for the UK air traffic network and dynamic airspace sectorisation.
Education
- 2022 – 2026PhD
Imperial College London
Publications
- Evaluation of Air Traffic Network Resilience: A UK Case Study(2024, Aerospace)
- Spatiotemporal Thunderstorm Forecasting for Pre-Tactical Air Traffic Operation: A Deep Learning Approach(2024, AIAA AVIATION FORUM AND ASCEND 2024)
- Enhancing air traffic operational efficiency by reducing network scale(2024, Aerospace Traffic and Safety)
- Robust 3D dynamic airspace sectorization: A multilayer graph-based approach(2026, Journal of Air Transport Management)
- Temporally Correlated Deep Learning-Based Horizontal Wind-Speed Prediction(2024, Sensors)