Geometry, topology and machine learning

The conference will serve as a gathering point for researchers interested in studying machine learning and deep learning from a geometric perspective and, more generally, a mathematical viewpoint, as well as applying geometric and mathematical tools in machine learning in a broad sense. Geometric is understood in a broad sense, encapsulating but not limited to algebraic and topological tools for continuous and discrete structures. 

This workshop follows a Geometry and Machine Learning held in Scalea, Italy, in 2024 and of Geometry and Machine Learning 2 held in Paris, France in 2025.

The conference will be held in Paris at Sorbonne Université, Paris, from May 18 to May 22, 2026.

To give a talk please fill in the following form : link to the form.

For any questions, please contact: gregoire.sergeant-perthuis@sorbonne-universite.fr 

Practical informations: 

Where: Room C404, CQSB, Building C, 4th floor.
Sorbonne Université
4 Place Jussieu, 75005 Paris

Metro Station: Line 10, or Line 7 metro station Jussieu.

To schedule your itinerary a useful link is here.

Confirmed speakers

Olga Anosova (University of Liverpool)
Tolga Birdal  (Imperial College London)
Frederic Cazals (Inria d'Université Côte d'Azur)
Levent Doğan (Faculty of Computer Science, Ruhr University Bochum)
Marzieh Eidi (SCaDS.AI and MPI-MIS)
Argyris Kalogeratos (Université Paris-Saclay, ENS Paris-Saclay, CNRS)
Jiayi Li (MPI-CBG)
Tony Lelièvre (Ecole Nationale des Ponts et Chaussées ENPC-IP Paris)
Johannes Lutzeyer (École Polytechnique)
Matilde Marcolli (Caltech)
Matthieu Montes (Sorbonne Université, CNRS)
Nina Otter (Inria Saclay)
Steve Oudot (Inria Saclay)
Edouard Oyallon (Sorbonne Université, CNRS)
Julien Tierny (Sorbonne Université,CNRS)
Josué Tonelli Cuento (Johns Hopkins University)
Santiago Velasco-Forero (Mines Paris PSL, CNRS).