ELLIS Unit Berlin
Scientific foundations in the fields of ML
Unit Mission
The ELLIS unit Berlin unit is hosted at BIFOLD. Its aim is to 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, chemistry and earth observation as well as medicine), (4) deep learning and (5) learning and inference with structure and priors.
Research Agenda
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 closely with BIFOLD, MATH+ 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 of 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.
Participating Institutions
NEWS
A benchmark for trustworthy clinical AI
A new study published in Nature Communications shows that today's pathology foundation models can be influenced by the origin of a tissue sample. Researchers at BIFOLD and Aignostics developed PathoROB, a first-of-its-kind benchmark to measure and reduce this bias, shaping how the next generation of pathology AI is built.
Photo recap: AI to accelerate scientific understanding
From May 26–29, 2026, ELLIS Unit Berlin and BIFOLD hosted the workshop "AI to accelerate Scientific Understanding" at the Forum Digital Technologies in Berlin, exploring how explaining and interpreting AI models can advance discovery across molecular science, medicine, geoscience, and beyond.
EVENTS
BIFOLD Summer School 2026
The 2026 Berlin Summer School on Artificial Intelligence and Society invites researchers and practitioners to explore the parameters which have to be considered when AI systems are designed to act autonomously. The programme will focus on fundamental questions at the interface between autonomous systems, trustworthy machine learning, and robotics, as well as deployment in critical areas such as healthcare and scientific infrastructures.
Members
Coordination
Partner Institutions
