M.J. (Marta) Ribeiro
M.J. (Marta) Ribeiro
Profile
Biography
Marta is originally from Portugal, where she studied Aerospace Engineer at Instituto Superior Técnico. After completing her Master in Avionics, Marta worked at Portugália Airlines as an Operations Engineer, and later at Simteq developing simulators for pilot Training, and at CGI developing on the Galileo Project for ESA. In early 2023, Marta completed her PhD at TUDelft entitled "Conflict Resolution at High Traffic Densities with Reinforcement Learning". Marta is current an Assistant Professor at Air Transport and Operations. Her research focusses on employing artificial intelligence/machine learning to optimize operations in aviation.
Awards
- 1st Place at EUROCONTROL's Innovation Masterclass Competition "Conflict Resolution with Reinforcement Learning"
- Best Paper at International Conference on Research in Air Transportation (2022) in the Safety Section for the paper "Improving Safety of Vertical Manoeuvres in a Layered Airspace with Deep Reinforcement Learning"
Projects
Current ProjectsTitle: Colossus
Website: NA
Description: COLOSSUS paves the way for future European aviation products and services which are designed in a truly holistic approach and to thus provide a major contribution to the digital transformation of aviation and air transportation in order to enable European competitiveness in a key industrial sector. The expected outcomes of COLOSSUS provide Europe’s aviation sector with the platform to develop new and breakthrough product and technology in a holistic system-of-systems approach.
Past projects:
Title: AW-Drones
Website: www.aw-drones.eu
Description: AW-Drones supports the rulemaking process for the definition of rules, technical standards and procedures for civilian drones to enable safe and reliable operations in the European Union. The project will achieve this target through 2 sub-goals: (1) providing a repository of technical standards and “best practices” to the drone community, and (2) proposing and validating with relevant stakeholders a set of technical standards to comply with existing regulation for drone operations.
Expertise
- Aircraft maintenance optimization (with a focus on condition-based maintenance).
- Disruption management for flights and maintenance operations;
- Scheduling of airline operations.
- Delays estimation.
- Application of artificial intelligence/machine learning techniques in aviation.
For all publications:
Link to pure: https://research.tudelft.nl/en/persons/mj-ribeiro
Link to google scholar: https://scholar.google.com/citations?user=5LvOlr0AAAAJ&hl=en
Link to researchgate: www.researchgate.net/profile/Marta-Ribeiro-10
Expertise
Publications
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2024
Aircraft Take-off Weight Prediction with Operational Data and Supervised Learning
A.I. Gheorghe / Junzi Sun / M.J. Ribeiro / Pascal Hop / Benjamin Cramet
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2024
Certification of Reinforcement Learning Applications for Air Transport Operations Based on Criticality and Autonomy
M.J. Ribeiro / I. Tseremoglou / Bruno F. Santos
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2024
Prediction of Non-Routine Tasks Workload for Aircraft Maintenance with Supervised Learning
H. Li / M.J. Ribeiro / Bruno F. Santos / I. Tseremoglou
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2023
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2023
Policy Analysis of Safe Vertical Manoeuvring using Reinforcement Learning: Identifying when to Act and when to stay Idle
D.J. Groot / M.J. Ribeiro / Joost Ellerbroek / J.M. Hoekstra
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Courses 2024
Courses 2023
Prizes
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2024
2024 AIAA SOFTWARE BEST PAPER
2024 AIAA SOFTWARE BEST PAPER “Certification of Reinforcement Learning Applications for Air Transport Operations Based on Criticality and Autonomy”
AIAA SCITECH 2024 Forum -
2023
3rd Place Young Scientist Award 2023
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2022
1st Place at EUROCONTROL's Innovation Masterclass Competition 2022
1st Place at EUROCONTROL's Innovation Masterclass Competition "Conflict Resolution with Reinforcement Learning"
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2022
Best Paper Award
Best Paper at International Conference on Research in Air Transportation (2022) in the Safety Section
10th International Conference for Research in Air Transportation
Ancillary activities
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2023-09-01 - 2025-08-29
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2023-03-01 - 2025-03-01