NEWS
Researcher Spotlight: Dr. Barış Büyüktaş
Petabytes of satellite data circle the Earth, locked in silos by legal and technical walls. Dr. Barış Büyüktaş is using federated learning to break them down, turning a scattered mountain of Earth observation data into a treasure trove for understanding our changing planet.
A benchmark for trustworthy clinical AI
A new study published in Nature Communications shows that today's pathology foundation models can be influenced by the origin of a tissue sample. Researchers at BIFOLD and Aignostics developed PathoROB, a first-of-its-kind benchmark to measure and reduce this bias, shaping how the next generation of pathology AI is built.
EVENTS
Lunch Talk: Dominik Naumann & Theekshana Dissayanake
In this Lunch Talk on "Toward AI-Enabled Cardiovascular Phenotyping in the Vehicle: The AutoHealth Study" Dominik and Theekshana will present the AutoHealth study. This study shows how in-car data collected across five cardiovascular cohorts contains sufficient physiological information to distinguish disease groups which enables AI-driven risk assessment.
Theory Meets Practice #5: Al for Precision Medicine: From Foundation Models to Tumor Tissue Profiling in Computational Pathology
Nearly every cancer diagnosis still begins with a pathologist examining a stained tissue slide under a microscope. Digital pathology turns those slides into gigapixel images — and with them, a uniquely demanding frontier for machine learning. But getting from raw pixels to clinically meaningful, quantitative insight about a tumor and its microenvironment is far from trivial.
*Data collected from 2020 onwards.
OPPORTUNITIES
BIFOLD welcomes job applications from interested parties year-round.
PUBLICATIONS
Gereon Dusella, Haralampos Gavriilidis, Volker Markl, Eleni Tzirita Zacharatou
Benchmarking Spatial Operations over Heterogeneous Data: The Case of Zonal Statistics
Yanqing Luo, Julius Hense, Niklas Prenißl, Andreas Mock, Klaus-Robert Müller, Thomas Schnake, Mina Jamshidi Idaji
Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology
Marco Morik, Xiao Ruiting, Shinichi Nakajima, Stefan Haufe, Ismail Huseynov
Structure-Preserving Correction Learning for Sparse Bayesian Inference in Brain Source Imaging
GRADUATE SCHOOL
Based on a highly competitive application process, the BIFOLD Graduate School offers an innovative fast-track PhD Program for students holding a bachelor’s degree, as well as a PhD Program for students with a master’s degree.
INSTITUTIONAL PARTNERS
ASSOCIATED PARTNERS
