Welcome

Thanks to all participants to the 2023-edition !!!!

Please consult the website of the 2025-edition (7-11 April 2025)

The link to the 2025-edition can be found here

2023 Spring School on Data-driven Model Learning of Dynamic Systems

Dates: Monday 3 April 2023 (beginning of the afternoon) - Friday 7 April 2023 (noon)

The Spring School consists of a five-days PhD course on data-based modeling (system identification) covering both the fundamentals and more advanced topics.

After two editions held in Nancy in 2017 and in 2018, one in Ecully in 2019, two virtual editions in 2021 and 2022 (due to the coronavirus pandemic), the 2023-edition will be the sixth edition of the Spring School on Data-driven Model Learning of Dynamic Systems.

The 2023-edition will be held in hybrid mode. Participants can thus attend the Spring School in person (on the campus of Ecole Centrale de Lyon) or virtually.

For this purpose, we will make use of the brandnew lecture hall of Ecole Centrale de Lyon that is completely dedicated to hybrid teaching. This lecture hall is located in the SKYLAB of Ecole Centrale (see here and here for more details and a video about this facility).

Like in the previous editions, the 2023-edition will welcome an international guest lecturer.

INVITED GUEST LECTURER FOR THE 2023-EDITION

Prof. Maarten SCHOUKENS, TU Eindhoven, The Netherlands

presenting a one-day course entitled

Nonlinear System Identification

Biography of the guest lecturer:

Research Profile: Maarten Schoukens is Assistant Professor in the Control Systems (CS) Group at the Department of Electrical Engineering, Eindhoven University of Technology. His main research interests include the measurement and data-driven modelling of nonlinear dynamical and linear parameter-varying systems using system identification and machine learning techniques, experimental design, and frequency domain methods in identification. Maarten was awarded an FWO Ph.D. Fellowship in 2011, and a EU - Marie Skłodowska-Curie Individual Fellowship in 2018. Maarten is co-organizer of the nonlinearbenchmark.org initiative promoting nonlinear system identification in general and the use of common datasets in data-driven nonlinear dynamical modelling research specifically.

Academic Background: Maarten Schoukens received the master’s degree in electrical engineering and the Ph.D. degree in engineering from the Vrije Universiteit Brussel (VUB), Brussels, Belgium, in 2010 and 2015 respectively. From 2015 to 2017, he has been a Post-Doctoral Researcher with the ELEC Department, VUB. In October 2017 he joined the Control Systems research group, TU/e, Eindhoven, The Netherlands as a Post-Doctoral Researcher, since 2018 he is an Assistant Professor in the same group.