Advances in low rank and model reduction methods for PDEs 

About the workshop

This workshop focuses on recent advances in low-rank techniques and model order reduction methods for the numerical approximation of partial differential equations. We will address theoretical developments, algorithmic strategies, and efficient computational frameworks for the simulation of large-scale and high-dimensional PDE problems, with applications ranging from parametric and multiscale models to uncertainty quantification and data-driven modeling. By bringing together leading experts and early-career researchers, the workshop aims to stimulate discussions on current challenges and emerging directions in reduced-order modeling.

The event is organized within the activities of the last thematic semester "PDE: Models, Analysis and Numerical Analysis", as part of the Excellence Department initiative (2023-2027) in the area of Mathematics and Computer Science, funded by the Italian National Agency for the Evaluation of Universities and Research Institutes.

Organizers

Alessandro Alla · Tommaso Taddei · Davide Torlo

Sponsors

• Department of Mathematics within Excellence Departments 2023-2027