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

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.

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".

AI robot excels in Olympic sport

A Deep Reinforced Learning framework, developed by BIFOLD Co-director Prof. Dr. Klaus-Robert Müller and his colleagues at Korea University, enabled the robot “Curly” to beat top-level athletes in the Olympic sport of curling.

Latest News

2021-03-24New workshop series “Trustworthy AI”

2021-03-22„European Data Sovereignty is a critical success factor“

2021-03-09Making the role of AI in Medicine explainable

2021-02-232020 Pattern Recognition Best Paper Award

2021-02-05BIFOLD Fellow Dr. Wojciech Samek heads newly established AI research department at Fraunhofer HHI

2021-01-15BIFOLD Co-Director Prof. Volker Markl named 2020 ACM Fellow

2021-01-13BIFOLD Research into Machine Learning for Molecular Simulation is among the Top 10 Most Downloaded Physical Science Articles in the Annual Reviews 2020

2021-01-12Resilient Data Management for the Internet of Moving Things: TU Berlin and DFKI Paper was Accepted at BTW 2021

Events

April2021

Trustworthy AI: Towards Auditable AI SystemsOnline workshop, organized by Dr. Samek. Part of a workshop series at the AI for Good Global Summit.

15:00 CETVirtual Event

April2021

CrocodileDB: Resource Efficient Database ExecutionTalk by Aaron J. Elmore (University of Chicago). Part of the DBMS research colloquium at TU Berlin.

16:00 – 16:45 CETVirtual Event

April2021

Trustworthy AI: Adversarial Attacks and DefencesOnline workshop, organized by Dr. Samek. Part of a workshop series at the AI for Good Global Summit.

15:00 CETVirtual Event

Mission Statement and Goals

BIFOLD, the Berlin Institute for the Foundations of Learning and Data aims to conduct research into the scientific foundations of Big Data and Machine Learning, to advance AI application development, and greatly increase the impact to society, the economy, and science.

BIFOLD will pursue the following strategic priorities in line with the German National AI Strategy:

Research: Conduct high-impact foundational research in the fields of Big Data, Machine Learning and their intersection, to profoundly advance the state-of-the-art in Big Data and Machine Learning methods and technologies as well as attract the world’s best scientists to Germany.
Innovation: Prototype AI technologies, Big Data systems, Data Science tools, Machine Learning algorithms, and support knowledge and technology exchange, to empower innovation in the sciences, humanities, and companies, particularly, startups.
Education: Prepare the next generation of experts in Big Data and Machine Learning, for future academic or industrial careers.