Replay available HERE

On Thursday 10th March, we held our monthly casual French Lab meeting referred to as the ‘AfterLab’ with Francisco “Paco” Chinesta, Professor of computational physics at ENSAM Institute of Technology (Paris, France) and director of the CNRS@CREATE DesCartes Program.

Francisco Chinesta is currently full Professor of computational physics at ENSAM Institute of Technology (Paris, France), Honorary Fellow of the “Institut Universitaire de France” – IUF- and Fellow of the Spanish Royal Academy of Engineering. He is the president of the ESI Group scientific committee and director of its scientific department. He was (2008-2012) AIRBUS Group chair professor and since 2013 he is ESI Group chair professor on advanced modeling and simulation of materials, structures, processes and systems. He received many scientific awards: IACM  Zienkiewicz award (New York, 2018), the ESAFORM award, … He is author of more than 350 papers in peer-reviewed international journals and more than 1000 contributions in conferences. He was president of the French association of computational mechanics (CSMA) and is director of the CNRS research group (GdR) on model order reduction techniques in engineering sciences, editor and associate editor of many journals. He received many distinctions, among them the Academic Palms, the French Order of Merit, … in 2018 the Doctorate Honoris Causa at the University of Zaragoza (Spain) and in 2019 the Silver medal from the French CNRS.  He is now the Director of the CNRS@CREATE DesCartes program – This program aims to develop disruptive hybrid AI to serve the smart city and enable optimized decision-making in complex situations for critical urban systems.

Prof Dominique Baillargeat, Scientific Executive Director of CNRS@CREATE, introduced CNRS@CREATE before Paco Chinesta’s intervention. 

To find out what Paco covered during this AfterLab, please take a look at his abstract below:

“DesCartes program: Informing and augmenting learning for empowering the  engineering of critical urban systems”

Informing And Augmenting Learning For Empowering The  Engineering Of Critical Urban Systems

Urban systems are too large, complex and uncertain to be approached by using physics-based models. At the same time fully data-driven models encounter several limitations, as the required amount of data, the capability of explaining decisions and the  ability of accessing to critical events. A hybrid approach combining knowledge and data, conciliates accuracy and rapidity in the diagnosis, prognosis and decision making, in a human-centric framework. Such hybrid approach can consist of informing or/and augmenting the learning. After introducing the DesCartes research program, the hybrid framework will be described and applied in two applicative domains: drone trajectory planning and remote sensing of industrial and civil infrastructures.

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