2027 Spring School on Data-driven Model Learning for Dynamic Systems

Hybrid Edition

The tenth edition of the doctoral school in data-based modelling (system identification) will be organised in hybrid mode. Participants can thus attend in person (on the campus of Ecole Centrale de Lyon, Ecully, France) or virtually. This school consists of a series of lectures and of exercise sessions aiming at covering the fundamentals of data-driven modelling approaches as well as more advanced topics. This course is eligible for scientific doctoral modules. The school is thus mainly aimed at an audience of PhD students, but is also open to any other persons interested in the topic of data-based modelling.

The 2027-edition will have the pleasure to welcome Kévin Colin (Université de Lorraine, France) that will present a course entitled:

Bayesian Estimation and Gaussian Processes

More information on this doctoral school (program, registration fees, accommodation, …) can be found at the following link:

https://spring-id-2027.sciencesconf.org/