Revisiting the frontiers of Scientific Machine Learning: where have we come from, and where should we go next? Join leading researchers at the University of Augsburg to reassess the field’s foundational priorities and shape the next research agenda for SciML.

Scientific Machine Learning (SciML) is transforming both scientific research and industrial applications by combining scientific computing with machine learning. Seven years after a foundational 2018 workshop identified six priority research directions for the emerging field, this workshop at the University of Augsburg brings together researchers from diverse disciplines to critically reassess these priorities in light of rapid technological advances.

Through expert keynotes, technical presentations, and interactive breakout sessions, participants will examine progress, identify emerging challenges, and explore new research opportunities across SciML. The workshop's outcomes will be synthesized into a collaborative scientific article, contributing to the ongoing development of the field and its future research agenda.