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Machine Learning| December 12, 2025

Test-of-Time Award for Konrad Rieck

Congratulations to BIFOLD Research Group Lead Konrad Rieck and his former colleagues. The Annual Computer Security Applications Conference (ACSAC) awarded the scientists the Test-of-Time Award for their publication "CUJO: Efficient Detection and Prevention of Drive by Download Attacks" (2010).

© Eisert
BIFOLD Update| December 11, 2025

Quantum Physicist Jens Eisert Joins BIFOLD as Fellow

Theoretical physicist Jens Eisert brings expertise in quantum computing and AI to BIFOLD’s Fellowship Program. His appointment advances Berlin’s efforts to link quantum research with machine learning.

© BIFOLD
Machine Learning| December 11, 2025

Gottfried Wilhelm Leibniz Prize awarded to Klaus-Robert Müller

Prof. Dr. Klaus-Robert Müller, co-director of BIFOLD and head of the Machine Learning Group at TU Berlin is honored with the Gottfried Wilhelm Leibniz Prize 2026, considered the highest honor for researchers in Germany. He is regarded as a pioneer of machine learning and has been driving this important area of artificial intelligence (AI) since 1989. His work combines excellence in formal mathematical reasoning with a strongly application-oriented approach.

BIFOLD Update| December 04, 2025

Reflections from the workshop “AI-based Methods for the Humanities”

From September 23 to 24, 2025, the workshop "AI-based Methods for the Humanities" explored how AI-based methods can advance research into history, culture, and language. The event was organized by the Max Planck Institute for the History of Science and BIFOLD.

©BIFOLD
Machine Learning| December 01, 2025

Rethinking how models "see"

Congratulations to BIFOLD researchers Tom Burgert, Oliver Stoll, and Begüm Demir from TU Berlin, and Paolo Rota from the University of Trento. They published a new study, that revisits a central claim in computer vision: so-called convolutional neural networks (CNNs) primarily rely on texture, rather than object shape, to recognize images. The publication was accepted as an oral presentation at NeurIPS 2025.

© BIFOLD / Setzpfandt
Explainable AI Machine Learning| November 28, 2025

Photo recap: AI in Medicine Workshop

Charité and BIFOLD hosted the “AI in Medicine” workshop in Berlin (Nov 24 - 25, 2025), bringing together leading experts on clinical AI, gene regulation modelling, medical LLMs and explainable AI to foster interdisciplinary collaboration between research and clinical practice.

BIFOLD Update| November 27, 2025

NeurIPS 2025 Conference Contributions

NeurIPS 2025 will be held in Mexico City and San Diego from November 30 to December 7, uniting leading experts in machine learning and computational neuroscience. BIFOLD is represented with 18 contributions, and one researcher has been recognized as a Top Reviewer.

© Amari
BIFOLD Update| November 19, 2025

Honorary Doctorate for Shun-ichi Amari

The TU Berlin has awarded an honorary doctorate to the eminent Japanese scientist Prof. Shun-ichi Amari in recognition of his groundbreaking contributions to the mathematical foundations of Artificial Intelligence. The honorary degree was presented to him by BIFOLD co-director Klaus-Robert Müller.

© Charité/BIFOLD
Machine Learning| November 14, 2025

AI Improves Lung Cancer Diagnostics

An interdisciplinary research team from BIFOLD (Berlin Institute for the Foundations of Learning and Data), Technische Universität Berlin, Universitätsklinikum Köln, Charité - Universitätsmedizin Berlin, the AI company Aignostics, and Ludwig Maximilians University Munich (LMU) has developed a novel AI-based method to more accurately predict the survival of lung cancer patients.

© Google DeepMind/BIFOLD
Machine Learning| November 13, 2025

When AI “thinks” like us

A team of researchers from BIFOLD, Google DeepMind, Max Planck Institute for Human Development and Max Planck Institute for Cognitive and Brain Sciences developed a new approach for image processing models, „AligNet“, that for the first time integrates human semantic structures into neural image processing models, bringing the visual understanding of these computer models closer to that of humans. Their publication „Aligning Machine and Human Visual Representations across Abstraction Levels“ has now been published in the prestigious scientific journal „Nature“.