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Researcher Spotlight: Dr. Haralampos Gavriilidis
From fixing a broken childhood computer to reshaping how the world shares information: Dr. Harry Gavriilidis is on a mission to make querying across disconnected databases faster, cheaper, and simpler, because in a data-driven world, fragmentation is a fundamental problem.
SaTML 2026 Conference Contributions
BIFOLD supports this year's IEEE SaTML, which is held from March 23 to 25 at the Technical University of Munich.
EDBT 2026 Conference Contributions
BIFOLD researchers will present several contributions at EDBT/ICDT 2026 in Tampere, Finland, including three research papers, three demos, and one workshop paper.
Klaus-Robert Müller honored with the Leibniz Prize
Germany's most prestigious research award, worth €2.5M, has gone to TU Berlin's machine learning pioneer. Müller's decades of work on support vector machines (SVM), deep learning, and explainable AI have shaped modern artificial intelligence.
Volker Markl elected to Leopoldina
Prof. Dr. Volker Markl, Co-Director of BIFOLD, Chair of Database Systems and Information Management group at TU Berlin and Head of the Research Department Intelligent Analytics for Massive Data at DFKI, has been elected as a member of the German National Academy of Sciences Leopoldina. With this election, the academy recognizes his outstanding scientific achievements in computer science as well as his contributions to the advancement of his field.
BIFOLD at WACV 2026
BIFOLD researchers of the Big Data Analytics for Earth Observation group will present GeoRank: a novel method that embeds geographical relationships into self-supervised learning for multispectral satellite imagery, consistently improving state-of-the-art algorithms.
Wasserstein distances made explainable
BIFOLD scientists developed a novel framework to make a widely used foundational statistical tool, the Wasserstein distance, interpretable in machine learning and data analysis contexts.
Symbolic XAI
Researchers at BIFOLD have been exploring how to make AI explain itself in the same way, people explain themselves. The team’s work focuses on making AI predictions as clear and intuitive as a human explanation.
Researcher Spotlight: Dr. Lukas Muttenthaler
What if AI could learn to see the world the way we do? BIFOLD PhD graduate Dr. Lukas Muttenthaler is pushing AI beyond raw performance, exploring representational alignment, where cognitive science meets computer vision to build machines that perceive more like humans.
Open-Source Award for DifferentiationInterface.jl
DifferentiationInterface.jl, co-developed by BIFOLD researcher Adrian Hill, wins one of France’s Open Science Awards for making cutting-edge modeling and optimization more flexible, efficient, and open.