AI Center x IBI - Distinguished Seminar Series - Prof. Fabian Theis

The talk is co-organized by the EPFL AI Center and the Institute of Bioengineering as part of their distinguished research seminar series and BioE series.

Hosting professors: Prof. Maria Brbic & Prof. Raphael Gottardo

Title
Decoding cellular systems: From observational atlases to generative interventions

Abstract
Over the past decade, the field of computational cell biology has undergone a transformation — from cataloging cell types to modeling how cells behave, interact, and respond to perturbations. In this talk, I will review and explore how machine learning is enabling this shift, focusing on two converging frontiers: integrated cellular mapping and actionable generative models. I’ll begin with a brief overview of recent advances in representation learning for atlas-scale integration, highlighting work across the Human Cell Atlas and beyond. These efforts aim to unify diverse single-cell and spatial modalities into shared manifolds of cellular identity and state. As one example, I will present our recent multimodal atlas of human brain organoids, which integrates transcriptomic variation across development and lab protocols. From there, I’ll review the emerging landscape of foundation models in single-cell genomics, including our work on Nicheformer, a transformer trained on millions of spatial and dissociated cells. These models offer generalizable embeddings for a range of tasks—but more importantly, they set the stage for predictive modeling of biological responses. I’ll close by introducing perturbation models leveraging generative AI to model interventions on these systems. As example I will show Cellflow, a generative framework that learns how perturbations such as drugs, cytokines or gene edits — shift cellular phenotypes. It enables virtual experimental design, including in silico protocol screening for brain organoid differentiation. This exemplifies a move toward models that not only interpret biological systems but help shape them.

Bio
Prof. Dr. Dr. Fabian J. Theis is internationally recognized for pioneering work at the interface of artificial intelligence, machine learning, and biomedicine. As Head of the Computational Health Center at Helmholtz Munich and Chair for Mathematical Models of Biological Systems at the Technical University of Munich, he leads cutting-edge research on multimodal data integration, single-cell and spatial omics, and AI-powered modeling of cell states in health and disease.
A founding force behind Helmholtz.AI and co-director of several national and European AI initiatives, Theis plays a key role in shaping the biomedical AI landscape. He is a core contributor to the Human Cell Atlas and has driven the development of widely adopted computational tools in the life sciences.
His achievements have been recognized with numerous honors, including the Gottfried Wilhelm Leibniz Prize (2023), the ISCB Innovator Award (2025), and an ERC Advanced Grant (2022). In 2025, he was elected to the German National Academy of Sciences Leopoldina and appointed Chair of the Bavarian AI Council.
Beyond academia, Theis actively advises biotech companies and drives translational AI research towards clinical applications and precision medicine.