After Cachan (2011, 2015), Blois (2013), Sevilla (2017) and Paris (2019 and 2023), we are planning to organize a new workshop devoted to recent advances in model reduction and related techniques and their potential impact in computational and prediction sciences, especially (but not only) in mechanical engineering.
Practical focus will be on recent developments in Reduced Basis (RB) approaches, Proper Orthogonal Decomposition (POD) and Proper Generalized Decomposition (PGD) methods for the numerical resolution of models involving partial differential equations. Other model order reduction methods such as those based on scientific machine learning technique, for instance, are welcome in order to foster cross-fertilization of ideas and their synergy.