Research interests
I am a research scientist with ONERA and Université de Toulouse.
My research interests include Data Science, Machine Learning and Decision Science applied to aviation, with a particular focus on optimisation, anomaly and pattern detection.
Applications range from air traffic management, operations, predictive maintenance, safety analyses and risk assessment.
Selected recent publications
See the full list of my publications.
See also on Google Scholar, ResearchGate, HAL, Scopus and SciProfiles.
https://orcid.org/0000-0002-2335-5774-
Michael Schultz, Judith Rosenow and Xavier Olive.
Data-driven airport management enabled by operational milestones derived from ADS-B messages.
Journal of Air Transport Management 99, 2022, 102164;
https://doi.org/10.1016/j.jairtraman.2021.102164 -
Xavier Olive and Luis Basora.
Detection and identification of significant events in historical aircraft trajectory data.
Transportation Research Part C: Emerging Technologies 119, 2020, 10237;
https://doi.org/10.1016/j.trc.2020.102737 -
Luis Basora, Xavier Olive and Thomas Dubot.
Recent Advances in Anomaly Detection Methods Applied to Aviation.
Aerospace, 6(11), 2019, 117;
https://doi.org/10.3390/aerospace6110117
Editorial board member
2022Co-editor in chief for the Journal of Open Aviation Science
2022Program Committee Member for the 10th OpenSky Symposium
2022Technical Committee Member for the 1st International Conference for CBM in Aerospace
2021 Guest Editor for MDPI Aerospace Special Issue Application of Data Science to Aviation II
2021Program Committee Member for the 9th OpenSky Symposium: proceedings, videos
2021 Editor for TU Delft OPEN Publishing
2021 Guest Editor for MDPI Aerospace Special Issue Application of Data Science to Aviation
2020 Technical Program Chair for the 8th OpenSky Symposium: proceedings, videos
Book
- Programmation Python avancée with Dunod Editions (in French)
Most active collaborations
- Luis Basora and Jérôme Morio, ONERA, Université de Toulouse 🇫🇷
- Benoit Figuet and Raphael Monstein, ZHAW, Zurich, Switzerland 🇨🇭
- Junzi Sun, Technical University of Delft, The Netherlands 🇳🇱
- Michael Schultz, Universität der Bundeswehr, München, Germany 🇩🇪
PhD students
2025
2022active Nicolas Huber starts working around hybrid trajectory generation methods for collision risk modelling (collaboration with ZHAW).
2025
2022active Kim Gaume starts working around data-driven methods and uncertainty for air traffic deconfliction methods (collaboration with ENAC).
2025
2022active Zakaria Ezzahed starts his research around explainable artificial intelligence for anomaly detection (collaboration with ENAC).
2024
2021active Timothé Krauth starts his research around trajectory generation and estimation of risk probability for aircraft collision (collaboration with ZHAW).
2021
2017graduated Sana Ikli defended her thesis around the Aircraft Landing Problem, entitled “Méthodes exactes et heuristiques pour l’ordonnancement des atterrissages d’avions”
(collaboration with ENAC and ISAE-SUPAERO).
Student assignments
2022graduated Arthur Viens starts working on Bayesian neural networks for anomaly detection and Remaining Useful Life (RUL) estimation.
2022graduated Michel Khalaf starts working on real-time turbulence information extraction from ADS-B data.
2021graduated Adrian Lafage graduated after a work on a trajectory generation framework.
2021graduated Raphaël Delair graduated after a work on ADS-B based airport collaborative decision making, with a particular focus on ground operations.
2020 Paloma Bry paper
Aircraft Fleet Health Monitoring with Anomaly Detection Techniques
2019 Benoît Viry paper
Deep Trajectory Clustering with Autoencoders
2018 Jeremy Grignard paper
Detecting Controllers’ Actions in Past Mode S Data by Autoencoder-Based Anomaly Detection
Open access projects (open source, open data)
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The traffic library provides data analysis methods commonly applied to trajectories and airspaces. It offers facilities to parse and/or access traffic data from open sources of ADS-B traffic like the OpenSky Network. It is designed to be easily extendable to other sources of data.
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The open aviation data initiative intends to reference any kind of (possibly open) data initiative related to aviation. It is supported by a group of academics, researchers and aviation people working to bring the power of data in order to improve the current state of the art in aviation.
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I am pretty active within the OpenSky Network, a non-profit association aiming at improving the security, reliability and efficiency of the air space usage by providing open access of real-world air traffic control data to the public.
