Data-based Materials Design

Research Focus

The research of the Data-based-Materials-Design group orbits around the development and application of AI methods for the modeling, design, and discovery of materials. Methods span compressed sensing, symbolic regression, subgroup discovery, and deep learning, while applications cover catalysis, characterization of surfaces, and several mechanical and transport properties of nano- as well as macro-scaled materials. Focus is on methods that yield interpretable models and can cope with “small data” for training. The group participates in the NFDI FAIRmat consortium, in particular in coordinating the creation of metadata and ontologies for the Interoperability and Reusability of FAIR (materials-science) data.

 

Email: luca.ghiringhelli@fau.de

Website: https://www.matsim.tf.fau.de/person/luca-ghiringhelli/