Research Seminar: Data science for intelligent operations of air transport systems

The aviation sector has always been technology driven. Yet the aviation sector has not been able to harness the power of big data and artificial intelligence (AI) as much as some other sectors. Targeting this opportunity, I develop analytical methods to improve the operations of air transportation systems with the use of large-scale data generated from real-world operations. These data include sensor values on aircraft components, airline operations status, as well as external information i.e., traffic congestion. It is a computational challenge to extract and model the dependences among diversified data sources effectively and efficiently. To tackle this challenge, I propose a new framework to integrate domain knowledge, physics/mechanism models and various AI technologies. In this talk, I will demonstrate how this framework can used for the design and operations of air transport systems via several examples, e.g. anomaly detection in flight data recorder data, modeling national air traffic network activities, etc.

Poster