Nicolas Durand

Nicolas Durand is a Professor at the National School of Civil Aviation (ENAC), specializing in Air Traffic Management through the integration of Metaheuristics, Combinatorial Optimization, and Interval Methods. His work focuses on hybridizing Evolutionary Algorithms with Machine Learning to enhance Conflict Resolution and Trajectory Prediction in aviation systems.

His research spans Unmanned Aerial Systems (UAS), ADS-B Data Analysis, and 3D Collision Avoidance. Recent projects include Behavior Cloning for conformal automation and Median Regression for lateral deconfliction. Collaborations with institutions like ONERA and ISAE-SUPAERO highlight his interdisciplinary approach.

Publications reveal a trend toward Explainable AI in ATM, with applications in Dynamic Conflict Resolution, Mass Estimation, and UAS Integration. His work bridges theoretical optimization (e.g., Global Optimization, Interval CP) with operational needs, emphasizing Controller Expertise and Uncertainty Quantification.