Towards Safe and Intelligent Air Traffic Operations

Air Transportation Modeling and Control Laboratory (ATMCL, Principal Investigator: Professor Keumjin Lee) conducts research on air traffic management (ATM), developing data-driven modeling and optimization methods for safer and more efficient aircraft operations, such as air traffic flow management, flgiht trajectory prediction, free route airspace, and advanced ATM technologies. ATMCL also studies unmanned traffic management (UTM), aiming to ensure safe low-altitude operations through geofencing, path planning, conflict management, and risk assessment frameworks.

Nahyun Kim, Hangyeol Seon, and Taejung Kwon are honored with a Grand Prize at the Land, Infrastructure and Transport AI Solution Challenge (Business Idea Competition) for their aviation insurance business idea. Big Congratulations!

The paper “Multi-Agent Inverted Transformer for Flight Trajectory Prediction” by Seokbin Yoon and Keumjin Lee is accepted at IEEE Transaction on Intelligent Transportation Systems. Congratulations!!

Kyungmin Kim won the AIAA SciTech 2026 Intelligent Systems Student Paper Competition for the paper  “Probabilistic Multi-Agent Aircraft Landing Time Prediction,” coauthored with Seokbin Yoon and Keumjin Lee. 

Seonggin Lee is honored with an Excellence Award at the Veterans Startup Competition hosted by the Ministry of Patriots and Veterans Affairs, South Korea, for his AI-driven Aviation startup. Huge congratulations!

The paper “Aircraft Trajectory Dataset Augmentation in Latent Space” by Seokbin Yoon and Keumjin Lee is accepted at International Journal of Aeronautical and Space Sciences. Congrats!