Research Engineer, Predictive Maintenance System for Railway Rolling Stock
After a Ph.D. in experimental robustness improvement for railway passengers access systems, he started working at IKOS in 2012, studying and designing predictive maintenance systems both for Bombardier (2012-2016) and SNCF (2016-today).
For 10 years he has designed, improved and deployed system expert based predictive maintenance systems. These systems are currently used to handle a fleet of more than 400 train in operation in the Paris area (France) by the SNCF.
In parallel he is overseing for IKOS Lab (R&D dept. of IKOS) the design and the development of a new learning predictive maintenance platform, called IKIM, which combines System Expert, Machine Learning, human in the loop and GMAO.