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Rethinking AI architecture for molecular simulations
Classical machine learning models for molecular dynamics embed physical principles, such as energy conservation and equivariance, directly into their architectures. These inductive biases have long been seen as essential for reliable simulations. A new study challenges this assumption with a surprisingly simple approach.
ICLR 2026 Conference Contributions
BIFOLD researchers will participate in the fourteenth International Conference on Learning Representations (ICLR), contributing seven workshop papers and seven posters.
Second BIFOLD Data Systems retreat
Researchers from four BIFOLD research groups gathered on April 7- 8 for their second annual retreat, spanning expertise from classical database management to modern data science processes.
New AI Method Enables More Precise Simulation of Complex Molecules
A new machine learning method enables global atomic interactions in chemical systems to be represented more efficiently. This could allow chemical and materials science processes to be simulated more accurately in the future, potentially accelerating the development of new drugs, more efficient batteries, and more sustainable materials.
BIFOLD appoints new Deputy Directors
BIFOLD appoints Prof. Dr. Begüm Demir, Prof. Dr. Konrad Rieck and Prof. Dr. Alexander Meyer, as BIFOLD Deputy Directors. With this decision, BIFOLD strengthens its leadership team and underlines its commitment to advancing cutting-edge research in data-driven technologies and machine learning.
Memphis paper receives 2026 ACM SIGMOD Research Highlight Award
The SIGMOD community honors the research of BIFOLD researchers Arnab Phani and Matthias Böhm. Their work on eliminating the inefficient reuse of intermediate computations across multi-backend machine learning systems addresses a key challenge at the intersection of data engineering and ML.
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.