Bifold – The Berlin Institute for the Foundations of Learning and Data

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Earth Observation Data for Climate Change Research

Sphere

In Search of Europe’s Scientific Identity

BIFOLD Fellow Dr. Matteo Valleriani uses algorithms to group and analyze digitized data from historical works. One of the goals of Valleriani’s research is to unlock the mechanisms involved in the homogenization of cosmological knowledge in the context of studies in the history of science.

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Making the role of AI in Medicine Explainable

BIFOLD researcher developed a new tissue-section analysis system for diagnosing breast cancer based on Artificial Intelligence. The system explains the Machine Learning decision process in the form of heatmaps.

Making the role of AI in Medicine Explainable

Molecule Manipulation

Building with Molecules

A cooperation project of FZ Jülich and Prof. Dr. Klaus-Robert Müller on manipulation of molecules through Reinforced Learning was announced as a Falling Walls Science Breakthrough of the Year in the category "Engineering and Technology".

Building with Molecules

Events

Sep2021

AI for Structured Data AnalyticsTalk by Beng Chin OOI (National University of Singapore) in the Database Management Systems Research Colloquium.
If you are interested in participating, please contact coordination@bifold.berlin.

10:00 – 10:45 CESTVirtual event

Sep2021

Kickoff: Virchow 2.0Kickoff event of the Virchow 2.0 cluster, a novel biomedical AI innovation ecosystem for the implementation of cell-based medicine in Berlin-Brandenburg.

09:00 – 20:00
CESTVirtual event

Latest News

2021-09-07New Type of Algorithm for Brain Research

2021-09-06Using Machine Learning in the Fight against COVID-19

2021-08-26SIGCOMM 2021 Best Paper: Internet Hypergiants Expand into End-User Networks

2021-08-13VLDB2021: BOSS Workshop features Open Source Big Data Systems

2021-08-10Earth Observation data for climate change research

2021-07-22BIFOLD welcomes the first six Junior Fellows

2021-07-07Higher impact through reproducibility

2021-07-01In Search of Europe’s Scientific Identity

Mission Statement and Goals

BIFOLD conducts foundational research in big data management and machine learning, as well as its intersection, to educate future talent, and create high-impact knowledge exchange.

The Berlin Institute for the Foundations of Learning and Data (BIFOLD), has evolved in 2019 from the merger of two national Artificial Intelligence Competence Centers: the Berlin Big Data Center (BBDC) and the Berlin Center for Machine Learning (BZML). Embedded in the vibrant Berlin metropolitan area, BIFOLD provides an outstanding scientific environment and numerous collaboration opportunities for national and international researchers. BIFOLD offers a broad range of research topics as well as a platform for interdisciplinary research and knowledge exchange with the sciences and humanities, industry, startups and society.

Data management (DM) and machine learning (ML) are the scientific and technical pillars powering the current wave of innovation in artificial intelligence (AI); it is the efficient processing and intelligent analysis of very large, complex, heterogeneous data that has the potential to revolutionize and substantially improve our lives and societies. BIFOLD conducts scalable yet agile foundational AI research. Furthermore, it addresses the emerging challenges and requirements created by the rapidly growing importance of data management and machine learning in practically all areas, from medicine, industry, natural sciences, humanities, e-commerce, and media, to government and society.