STEAM Academy Seminar: Topological Deep Learning for the Next Generation of AI4Science

by Prof. Tolga Birdal (Imperial College London)

Thursday 2 Jul 2026, 14:30 → 16:00 Europe/Zurich

500/1-001 - Main Auditorium (CERN)

Abstract: Deep learning transformed artificial intelligence by exploiting structure. Convolutions leveraged the geometry of images, transformers leveraged the structure of sequences, and graph neural networks enabled learning on relational data. Yet many scientific systems—from particle interactions and physical fields to molecular assemblies, cellular processes, and complex engineered systems—cannot be faithfully described by pairwise relationships alone. Their behavior emerges from higher-order interactions, multiscale organization, and topological constraints.

This talk argues that topology is becoming the next organizing principle of AI4Science. Tolga will introduce Topological Deep Learning, a rapidly emerging framework that extends machine learning beyond graphs toward richer topological domains capable of representing interactions among groups, motifs, cycles, surfaces, and higher-dimensional structures. He will explore recent advances in higher-order message passing, sheaf learning, topological neural networks, neural operators, and transformer architectures under a common perspective.

Tolga will then demonstrate how these ideas enable new capabilities across scientific discovery, including molecular foundation models, topology-aware generative models, learning on biological and physical systems, and operator learning for scientific simulation, presenting an emerging scientific ecosystem from challenges and opportunities to open source software.

Bio: Dr. Tolga Birdal is an assistant professor (Lecturer) and a UKRI Future Leaders Fellow in the Department of Computing of Imperial College London. Previously, he was a senior Postdoctoral Research Fellow at Stanford University within the Geometric Computing Group of Prof. Leonidas Guibas. Tolga has defended his masters and Ph.D. theses at the Computer Vision Group under Chair for Computer Aided Medical Procedures, Technical University of Munich led by Prof. Nassir Navab. He was also a Doktorand at Siemens AG under the supervision of Dr. Slobodan Ilic working on “Geometric Methods for 3D Reconstruction from Large Point Clouds”. His thesis was awarded the prestigious EMVA Young Professional Award. His current foci of interest involve topological / geometric machine learning and 3D computer vision. His more theoretical work is aimed at investigating and interrogating limits in geometric computing and non-Euclidean inference as well as principles of deep learning. Tolga has several publications at well-respected venues such as NeurIPS, CVPR, ICCV, ECCV, ICLR, T-PAMI, ICRA, IROS, ICASSP and 3DV. He is AC for CVPR, ICCV, ECCV and is currently program-chairing 3DV 2025. Aside from his academic life, Tolga has co-founded multiple companies including Befunky, a widely used web-based image editing platform.

 

This seminar is part of the CERN STEAM Academy Seminar Series. 

A networking coffee break will follow the seminar.

A public webcast will be available and accessible to external participants.

 

With the support of CERN's Next Generation Triggers Project.

Recording