EVENTS

This symposium aims to bring together researchers from the interdisciplinary fields of machine learning and data-driven methods with mechanical dynamics to foster  collaboration and promote the adoption of hybrid algorithms in engineering applications. We anticipate presentations from academic institutions and industry, reflecting the growing prominence of data-driven approaches in science-based decision-making.  Topics of interest include, but are not limited to:

• Data-driven analysis and modeling of dynamics
• Physics-constrained learning
• Learning-based system identification
• Data-enhanced physical simulations
• Industrial applications of deep learning for engineering dynamics
• Data Science
• Data-based control
• Error bounds and guarantees in data-based methods

We look forward to receiving contributions to this mini-symposium for a lively exchange in this important aspect of research!

Abstract submission is currently open until April 17, 2025. Further instructions and templates are available on the conference homepage: https://colloquia.gacm.de/organisation.

Institutions

• German Association for Computational Mechanics (GACM)