Rate My Professor Sameer Alam

Alam's research at UNSW centered on artificial intelligence and simulation for air traffic management, including development of the Air Traffic Operations and Management Simulator (ATOMS), the first system integrating air traffic modeling with aircraft noise and emissions data to enable direct flight paths, reducing fuel consumption by up to 500 kg and noise by 35% on typical Sydney-Melbourne Boeing 747 flights. His work addressed airspace collision risk hot-spot identification, Australian airport network robustness via complex network analysis, ADS-B vulnerabilities, dynamic airspace sectorization, and lateral airway offset optimization using differential evolution. Key publications include "A complex network approach towards modeling and analysis of the Australian Airport Network" (2017), "Identification of ADS-B system vulnerabilities and threats" (2010), "A multi-objective approach for dynamic airspace sectorization using agent based and geometric models" (2012), "Atoms: Air traffic operations and management simulator" (2008), and "Predictive classification and understanding of weather impact on airport performance through machine learning" (2021). He received the 2011 ACT Young Tall Poppy of the Year Award, ANU Science Medal, and 2008 Fresh Science Award for his contributions to safer, greener aviation. Alam authored over 200 peer-reviewed publications, earned multiple best paper awards, and consulted for ICAO and others, impacting global air traffic safety and efficiency.