From October 7 to 10, 2025, the University of Stuttgart will host the Research Frontiers Workshop on Scientific Machine Learning, organized by SimTech. This highly interactive event brings together researchers from across disciplines to explore a critical and emerging space at the intersection of machine learning (ML) and scientific inquiry.
The workshop focuses on what organizers refer to as the “Bermuda Triangle” of ML in science, where three complex and interdependent challenges meet:
- Knowledge Infusion
- Explainability
- Scientific Discovery
Participants will engage deeply with fundamental questions:
- How can AI offer genuine understanding, not just predictions?
- Can machine learning generate serendipitous scientific insight?
- How can we reach interpretability rooted in domain-specific knowledge?
Over four days, internationally renowned experts will deliver keynote lectures, and participants will collaborate in plenary discussions, breakout sessions, and interdisciplinary debates. A central aim is to uncover and structure the often-hidden foundational concepts behind ML methods — such as information processing, complexity, and the nature of knowledge — and to reflect critically on which developments truly advance scientific understanding.
The workshop fosters a culture of open, cross-disciplinary exchange, bringing together voices from physics, engineering, artificial intelligence, and the philosophy of science. By encouraging dialogue beyond disciplinary silos, the event seeks to spark “blue skies” thinking and inspire new directions for research that might not emerge within isolated fields.
Participants can look forward to:
- Keynote talks by internationally recognized experts
- Interactive sessions for in-depth exchange and critical reflection
- A vibrant, collaborative atmosphere aimed at building bridges between disciplines
The Research Frontiers Workshop on Scientific Machine Learning is funded by the Cluster of Excellence “Data-Integrated Simulation Science (SimTech)”, the German Research Foundation (DFG), the Cluster of Excellence “Machine Learning: New Perspectives for Science”, and the Heidelberg Academy of Sciences and Humanities.
Applications are open until August 31, 2025.