We are a research group at the University of Fribourg, working at the intersection of geometry, topology, and machine learning.
Grounded in mathematics, we build principled methods that reveal hidden structure in complex data.
If you are a student at the University of Fribourg and are interested in writing a bachelor’s or master’s thesis with us, please drop us a line.
What We Do
Data has shape, and we build tools that find it.
Our core focus is geometrical and topological machine learning, i.e., developing methods that make use of principles from geometry and topology to learn robust, expressive representations. We work with concepts like Euler Characteristic Transforms, persistent homology, discrete curvature, and metric space magnitude to analyze point clouds, graphs, and manifolds.
We see ourselves as toolsmiths, caring about theory and practice alike.
“AIDOS” carries two meanings. The first one describes our work, i.e., Artificial Intelligence for Data-Oriented Science. The second one originates from the ancient Greek word “αἰδώς,” which denotes a sense of awe, reverence, or humility when facing something greater than oneself. This awe keeps us honest about the many things we do not (yet) know, and we strongly believe that this is the right disposition for doing science.
