Manifold Learning : Model Reduction in Engineering

David Ryckelynck is working on model-based/physics-based engineering assisted by machine learning. He did seminal works on hyper-reduction methods, in the field of applied mathematics and computational mechanics. He is the head of a lecture on Ingénierie Digitale Des Systemes Complexes (Data Science for Computational Engineering) at Mines Paris PSL University.
Fabien Casenave is a research scientist at Safran Tech, the research center of Safran Group, a French multinational company that designs, develops and manufactures aircraft engines, rocket engines as well as various aerospace and defense-related equipment or their components. As head of the Physics-Informed AI and Numerical Experiments team, Fabien has been working on model-based/physics-based engineering assisted by machine learning applied to industrial design challenges in structural mechanics.

Nissrine Akkari is a research scientist at Safran Tech. She has been working on model-based/physics-based engineering assisted by machine learning applied to industrial design challenges in computational fluid dynamics.