Fast Solution Methods for Wave Propagation Problems: From Classical Domain Decomposition Solvers to Learning
Wave propagation and scattering problems are of huge importance in many applications in science and engineering - e.g., in seismic and medical imaging and more generally in acoustics and electromagnetics.
Overview
Abstract
Wave propagation and scattering problems are of huge importance in many applications in science and engineering - e.g., in seismic and medical imaging and more generally in acoustics and electromagnetics. Large-scale simulations of those applications are one of the hard problems from a computational point of view since requires an interplay between the parsimonious but sufficiently accurate discretisation methods and more sophisticated solution methods. Our aim is to show on one side, how classical domain decomposition methods developed in the latest years coupled with carefully chosen discretisations can help in this endeavour. On the other side, we would like to propose some openings towards the very attractive package of approximation-solution-optimisation offered by the new methods in scientific machine learning.
Brief Biography
Victorita Dolean just joined TU Eindhoven as a Full Professor in Scientific Computing. Before that, she was a part-time Professor at the University of Strathclyde, Glasgow, where she still holds a honorary visiting position. She is also a Fellow of the Institute of Mathematics and its Applications (IMA).
She did her PhD thesis at INRIA (France) in CFD using domain decomposition and parallel computing and subsequently became a research assistant at CMAP of Ecole Polytechnique in Paris. She got her first lecturer position at Evry University in Paris area, before moving to the University of Nice (now University Côte d’Azur). She also spent one year and a half as a visiting professor at the University of Geneva in Switzerland.
She works on the design of fast algorithms for the simulation of complex systems of PDEs with a focus in the latest years on wave propagation problems. Together with her collaborators, she was the recipient of Bull-Joseph Fourier Prize, delivered by Atos-Bull, for her innovative work on real time simulation of strokes using HPC (SIAM News, 2016). She co-authored a reference work on Domain decomposition methods (published by SIAM in 2015). She’s a member of the editorial board of SIAM Journal on Scientific Computing and of the Scientific Committee of International Conferences on Domain decomposition methods.
