Collaborations

The chair cooperates with national and international research institutions to develop solutions for the challenges in the aviation system. Current topics include efficient arrival management, automated airport aprons, and data-driven analysis of the air traffic system. As a result of these substantial collaborations, scientific publications have been and continue to be published in high-impact journals. These are the latest publications:

 

A combined optimization–simulation approach for modified outside-in boarding under COVID-19 regulations including limited baggage
M Schultz, M Soolaki, M Salari, E Bakhshian. Journal of Air Transport Management 106, 102258

A Deep Reinforcement Learning Approach for Airport Departure Metering Under Spatial–Temporal Airside Interactions
H Ali , DT Pham , S Alam , M Schultz. IEEE Transactions on Intelligent Transportation Systems, 2022, 1-18.

Towards a greener Extended-Arrival Manager in air traffic control: A heuristic approach for dynamic speed control using machine-learned delay prediction model
Lim Zhi Jun, Sameer Alam, Imen Dhief, Michael Schultz (2022). Journal of Air Transport Management 103, 102250

Data-driven airport management enabled by operational milestones derived from ADS-B messages
M Schultz, J Rosenow, X Olive (2022). Journal of Air Transport Management 99, 102164

Modeling Aircraft Departure at a Runway Using a Time-Varying Fluid Queue
E Itoh, M Mitici, M Schultz (2022). Aerospace 9 (3), 119

Implementation of a Long-Range Air Traffic Flow Management for the Asia-Pacific Region
M Schultz, D Lubig, E Asadi, J Rosenow, E Itoh, S Athota, V Duong (2021). IEEE Access 9, 124640-124659

Predictive classification and understanding of weather impact on airport performance through machine learning
M Schultz, S Reitmann, S Alam (2021). Transportation Research Part C: Emerging Technologies 131, 103119

Optimized aircraft disembarkation considering COVID-19 regulations
M Schultz, M Soolaki (2021). Transportmetrica B: Transport Dynamics, 1-21

Analytical approach to solve the problem of aircraft passenger boarding during the coronavirus pandemic
M Schultz, M Soolaki (2021). Transportation Research Part C: Emerging Technologies, 102931

International research partners

 

Prof. Eri Itoh
The University of Tokyo

Prof. Eri Itoh

Eri Itoh received a Ph.D. degree in Aeronautics and Astronautics from The University of Tokyo, Japan, in 2007. After gaining research experiences at Eurocontrol experimental centre, Netherlands Aerospace Center NLR, NASA Ames Research Center, and Nanyang Technological University, she currently holds positions of Professor at the Research Center for Advanced Science and Technology of The University of Tokyo, Professor at the Aeronautics and Astronautics Department of The University of Tokyo, and Chief Researcher at the Air Traffic Management Department of the Electronic Navigation Research Institute, National Institute of Maritime, Port and Aviation Technology. Her research interests cover designing mobility systems, especially automation systems that support human operators in air traffic management, including airspace and airport operations. Combining data-driven analysis, mathematical modelings, and simulation experiments, she works toward realizing even more resilient and eco-friendly air traffic operations. She also has interests in extending these approaches into next-generation mobility systems.

Prof. Duong Nguyen Vu
Nanyang Technological University - NTU Singapore

Prof. Duong Nguyen Vu

Vu Duong is Professor at School of Mechanical & Aerospace Engineering and Director of Air Traffic Management Research Institute of Nanyang Technological University (NTU), Singapore. Prior to the assignment at NTU, he had been Founding-Director of John von Neumann Institute, Viet Nam National University Ho Chi Minh City (VNU-HCM). He joins VinUniversity as Honorary Dean of College of Engineering and Computer Science and has also been appointed Advisor to Vietnam Minister of Planning and Investment on Innovation Strategy.

Prof. Duong had been Head of Innovative Research then Senior Scientific Advisor at the European Organization for Safety of Air Navigation – EUROCONTROL (1995-2012), and a member of the European Commission’s SESAR JU Scientific Committee (2010-2012). During his service time with EUROCONTROL, he had been at the origin of the works that led to the innovative Airborne Separation Advisory System, Airborne Autonomous Operations, Sector-less Flight-Centric Air Traffic Management (ATM) as well as several foundations for Air Traffic Flow Management. He was the founder or co-founder of 3 most prestigious conference series in Air Traffic Management and Air Transportation and 2 conference series in ICT and Artificial Intelligence. His research interest lies in the cornerstone of Machine Learning data-driven models, optimization, and automation for ATM. He has published more than 100 articles in peer-reviewed journals and conferences, and has supervised more than 20 Doctoral Theses in Operations Research, Systems and Computer Science applied to Air Traffic Management.

Prof. Sameer Alam
Nanyang Technological University - NTU Singapore

Prof. Sameer Alam

Sameer Alam is passionate about how Machines can learn and how Machines can perform higher order Cognitive tasks in safety critical domains such as Air Traffic Management. Sameer is the Deputy Director of Air Traffic Management Research Institute (ATMRI) and Co-Director of SAAB-NTU Joint Research Lab, where he leads 30 research scientists and 6 PhD students in the area of AI/Machine Learning for Air Traffic and Airport Operations. Prof. Alam has over 20 years’ experience in the design and development of Artificial Intelligence/Machine Learning models for Air Traffic Management and Airport operations. He has worked with various organizations including ICAO Middle-East, NASA Ames USA, AirServices Australia, CAAS Singapore, Eurocontrol, Civil Aviation Affairs Bahrain, and ENAC France. He also serves as a technical advisor to the Middle East Regional Monitoring Agency of the ICAO, technical advisor to the Ministry of Transport Bahrain, Editorial Board Member of Elsevier Transportation Research Part-C, and Program Committee member for the US & Europe ATM R&D Seminar. His research interest is in AI-Human Hybrid systems, Generative Adversarial Networks, Multi-Agent Reinforcement Learning, Deep Learning, Evolutionary Computation, and Complex Networks. He has invented/co-invented, with his students, several AI/Machine Learning algorithms for open research problems in Air Transportation.

Dr. Xavier Olive
Office National d'Etudes et de Recherches Aérospatiales (ONERA)

Dr. Xavier Olive

Xavier Olive graduated from Supaero, Université de Toulouse, France, and holds a PhD from Kyoto University, Japan. He is currently a research scientist at ONERA, passionate about aviation, maps, and data. His research interests include Data Science, Machine Learning and Decision Science applied to aviation, with a particular focus on optimization, anomaly, and pattern detection applied to air traffic management, operations, predictive maintenance, safety analyses, and risk assessment. Xavier also teaches artificial intelligence and advanced programming in Python to graduate students. He is the main author of the open-source traffic Python library, and of the book Programmation Python avancée with Dunod editions.

Dr. Majid Soolaki
University of Westminster

Dr. Majid Soolaki

Majid Soolaki is a research fellow within the School of Architecture and Cities at the University of Westminster. His research interests include Operations Research, Mathematical Modelling, Optimization, Air Traffic Management, and Supply Chain Management. He is working on research projects funded by the European Commission within the Horizon 2020 (SESAR ‘exploratory research’) programme, such as “NOSTROMO”.  Also, he was involved in lecturing at the University College Dublin, Ireland as a postdoctoral researcher. He continues to expand the future modeling capabilities of the air traffic management team with his expertise.