Research interests

My thesis concerns the study of Markov Decision Processes (MDPs) and its applications to predictive maintenance.
It deals with the modeling of a fleet of equipment which may fail or be required for missions on a random basis.
Thales wishes to set up an optimized and automated fleet management policy.
This work aim is to develop theoretical and numerical tools for solving such optimization problems.

Oral presentations

• June 2019 - 51èmes Journées de Statistique - JdS Nancy, France:
  Optimal predictive maintenance policy for multi-component systems.



• June 2019 - 7ème rencontre scientifique Sherbrooke-Montpellier - Sherbrooke, Canada:
  Politique de maintenance prédictive optimisée pour les systèmes multi-composants.



• September 2019 - 29th European Safety and Reliability Conference - ESREL Hannover, Germany:
  Optimal predictive maintenance policy for multi-component systems.