The need for immediacy and great degrees of interaction in many industrial and academic applications has forced the development of reduced order approaches for many problems of interest. In the last decade an impressive effort of research has been made by our community towards the successful development of such techniques. With the irruption of the industry 4.0 paradigm and the ubiquitous placement of sensors (e.g., Internet of Things, IoT), this turned out in the need of (big) data assimilation.
Going one step further, there is a growing interest on the development of techniques able to perform rapid computations supported by or based solely on data, without the need for any model or related, often costly, numerical computations.
This session is intended to be a place for the exchange of the latest results in the field of model order reduction, data-driven surrogates and hybrid techniques. Among the possible topics of interest, we cite the following (non-exhaustive) list of themes: