NEWS
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.
EVENTS
kennedy+swan: The Red Queen Effect
Starting January 26, 2026, the foyer of the Rahel Hirsch Center will host a new exhibition dedicated to a topic central to research at BIH and Charité: Artificial Intelligence.
AI Research vs AI Industry
Join Women in AI and ML6 on March 12th, 2026 for an interactive evening exploring “AI Research vs. AI in Industry: Similarities, Differences, and Everything In Between.” where cutting-edge research meets real-world impact.
*Data collected from 2020 onwards.
OPPORTUNITIES
BIFOLD welcomes job applications from interested parties year-round.
PUBLICATIONS
Carlos Enrique Muñiz-Cuza, Matthias Böhm, Torben Bach Pedersen
CAMEO: Autocorrelation-Preserving Line Simplification for Lossy Time Series Compression
Aaron Louis Eidt, Nils Feldhus
Simplifying Outcomes of Language Model Component Analyses with ELIA
Laure Ciernik, Agnieszka Kraft, Florian Barkmann, Josephine Yates, Valentina Boeva
Robust and efficient annotation of cell states through gene signature scoring
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
