Unit Berlin

The ELLIS unit Berlin unit will drive forward the following five priority research areas: (1) explainable AI, (2) scalable machine learning and data management, (3) machine learning for the sciences (in particular physics and chemistry, as well as medicine), (4) deep learning and (5) learning and inference with structure and priors.)

The goal of the ELLIS unit Berlin is to provide the scientific foundations in the fields of ML and, as a result, advance AI applications to yield a substantial benefit and progress for society, economy, and the sciences. The ELLIS unit Berlin collaborates with existing projects, such as BIFOLD, MATH+ and Science of Intelligence , and multiple graduate schools (Graduiertenkolleg) and collaborative research centers, established by the German Research Foundation (DFG).
 
By cooperating with universities in the Greater Berlin Metropolitan Area (e.g., Charite, FU Berlin, HU Berlin, TU Berlin, University Potsdam), scientific associations and societies as well as institutes of applied research (e.g., acatech, BBAW, DFKI, Fraunhofer, Helmholtz, Leibniz, Leopoldina, Max Planck, Max Delbrück Center) as well as with companies and startups, the ELLIS unit Berlin will help to spark innovation in a broad spectrum of applications in the sciences and industry.