Materials Data Science and Informatics (IAS-9)

The Institute for Materials Data Science and Informatics (IAS-9) develops advanced Machine Learning (ML) & Artifcial Intelligence (AI) methods tailored to challenges in the physical sciences and engineering. Our work bridges data-driven approaches with domain knowledge to push the boundaries of scientific discovery.

We are a multidisciplinary team of experts in ML and AI. Our group brings together ML engineers, AI researchers, data scientists, research software engineers, and domain scientists with a shared focus on scientific machine learning. Together, we develop and apply ML methods to tackle key challenges in the physical sciences and engineering: from accelerating simulations with surrogate models to extracting insights from complex imaging data, and building approaches that transfer across domains.

From high-throughput experiments to simulation pipelines, we address critical challenges in learning, data management, and reuse - embracing FAIR principles and "Data for AI" to advance sustainability and reproducibility in science.

Director: Prof. Dr. Stefan Sandfeld