Dagstuhl-Seminar — Automated Machine Learning for Computational Mechanics

Automated machine learning (AutoML) aims to reduce the need for experts to obtain effective ML pipelines. It offers off-the-shelf solutions that can be applied without prior knowledge in ML, allowing engineers to dedicate more time to domain-specific tasks. Regrettably, AutoML is underutilized in computational mechanics. There is almost no communication between the two communities, and engineers spend unnecessary effort selecting and configuring ML algorithms. In light of this, the current Dagstuhl Seminar is dedicated to fostering cross-pollination between the fields of AutoML and Computational Mechanics. It aims to convene a curated selection of international experts, each hailing from diverse backgrounds and various application domains, encompassing computer science, machine learning, engineering, mathematics, operations research, and industrial applications.