Academics−Engineers Meeting, 2nd Edition

The second edition of the Academics−Engineers Meeting entitled “Seizing motion: describe and infer system dynamics” will be held on the 25th of november 2020 online (with teams, register by email  seminaire@phimeca.com to get the connexion link).

The topic is describe (in french) at https://seminaire.phimeca.com and below.

Our objective is to gather academics and engineers around a wide thematics so as to spread methods and confront them issues from the engeeniring world.

Subscription is free but mandatory, by email at seminaire@phimeca.com.

Sylvain Girard

Phimeca, Équipe Fiabilité et Robustesse de Paris

Seizing motion: describe and infer system dynamics

  - « Langages de descriptions ou langages d'action ? » par Gilles Dowek (Inria)

  - « Neural networks & dynamical systems: dealing with partially-observed systems » par Ronan Fablet (IMT Atlantique)

  - « Identification de systèmes dynamiques par approches de type DMD » par Florian De Vuyst (UTC Compiègne)

  - « Problème a 3/N corps et missions spatiales vers les points de Lagrange » par Éric Joffre (European Space Agency)

  - « Data-driven discovery and uncertainty quantification of turbulence models for Fluid Dynamics » par Paola Cinella (Sorbonne Université)

  - « Calcul de complexité de trafic aérien à l'aide de modélisations basées sur les systèmes dynamiques » par Daniel Delahaye (ENAC)

A few equations are enough to fully describe a trajectory, either spatial or abstract.

However, the phenomena that engineers deal with are often so complex or ill known that it is impossible to deduce such equations straight from physical principles.

It is then necessary to draw upon a host of disciplines: optimisation, probability, signal processing, machine learning, topology…

The reasoning then becomes increasingly inductive, from parameter estimation up to completely giving up of analytical description and thinking the system as a black box.

This second edition of the Academics−Engineers Meeting will confront perspectives on the ways to depict, predict or even control the behaviour of dynamic systems.