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GeUmetric Deep Learning Workshop 2026

 

We are pleased to again welcome researchers to Umeå University for a workshop exploring different aspects of the vast and rapidly developing field of geometric deep learning. We aim to bring together researchers working at the intersection of physics, mathematics and deep learning, combining geometry and machine learning with a variety of different approaches. In this third installment, we have an explicit aim to highlight the use of geometrical methods in scientific machine learning.

The conference will feature invited talks by international experts and contributed research talks from the participants. Graduate students will be given priority in the selection of contributed talks. Our aim is to give young researchers the opportunity to present their research in a specialized but informal atmosphere

 

Invited speakers

Andreas Ipp, TU Wien
Vishal Ngairangbam, Durham University
Juan Viguera Diez, AstraZeneca

 

Registration

The workshop has a maximum number of participants. Registration is on a first-come, first-served basis via the form below.

Registration form - GeUmetric Deep Learning Workshop 2026

 

Dates: August 17-19, 2026 (lunch-to-lunch)

Location: NAT.D.300, Naturvetarhuset, Umeå University

For inquiries, please contact the organizing committee.

 

Program

View the full program: GeUmetric Deep Learning Workshop 2026 Program

 

Getting to the university

If you’re travelling by train, you should get off at Umeå Östra and take the escalator exit (on the side of track 2). Then you’re a 5 minute walk from Naturvetarhuset.

If you’re travelling with plane, there is a frequent bus service from the Airport to Vasaplan. From there, take bus 5,8, or 9 to Universum, or 1 to Universitetssjukhuset.

Please note that the workshop takes place before the semester starts, so that all buildings will be locked. If you’re arriving a lot earlier than the start of the conference, please notify the organizers so that they can let you in.

 

Previous workshops

GeUmetric Deep Learning 2024
GeUmetric Deep Learning 2025

 

Latest update: 2026-06-16