Welcome

 

 

Thanks to all participants to the 2022-edition !!!!

 

Please consult the website of the 2024-edition (8-12 April 2024)

 

 The link to the 2024-edition can be found here

 

 

 

2022 Spring School on Data-driven Model Learning of Dynamic Systems

Dates: Monday 4 April 2022 (beginning of the afternoon) - Friday 8 April (end of the afternoon)

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, one virtual edition in 2021,  the 2022-edition will be the fifth edition of the Spring School on Data-driven Model Learning of Dynamic Systems.

Due to the uncertainties related to the coronavirus pandemic, the 2022-edition will also be held in a fully virtual fashion.

Like in the previous editions, the 2022-edition will welcome an international guest lecturer.

 

INVITED GUEST LECTURER FOR THE 2022-EDITION

Prof. Håkan HJALMARSSON, KTH Stockholm, Sweden

presenting a one-day course entitled

Dynamic model learning

Hjalmarsson_Photo_2.jpg

 Biography of the guest lecturer: Håkan Hjalmarsson was born in 1962. He received the M.S. degree in Electrical Engineering in 1988, and the Licentiate degree and the Ph.D. degree in Automatic Control in 1990 and 1993, respectively, all from Linköping University,  Sweden.  He has held visiting research positions at California Institute of Technology, Louvain University and at the University of Newcastle, Australia.  He has served as an Associate Editor for Automatica (1996-2001), and IEEE Transactions on Automatic Control (2005-2007) and been Guest Editor for European Journal of Control and Control Engineering Practice. He is Professor at the School of Electrical Engineering, KTH, Stockholm, Sweden. He is an IEEE Fellow and past Chair of the IFAC Coordinating  Committee CC1 Systems and Signals. In 2001 he received the KTH award for outstanding contribution to undergraduate education. His research interests include system identification, signal processing, control and estimation in communication networks and automated tuning of controllers.   

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