Stathis Megas
Medical University of Vienna
“Uncovering hidden causes in biology using mathematical physics”
Host: Thomas Vogl
Programm
Understanding how genetic, cellular, and environmental perturbations propagate through tissues is a central challenge in biology. I will present new AI models of Virtual Cells and Virtual Tissues that combine causal inference, generative modeling, and ideas inspired by theoretical physics to disentangle biological mechanisms from confounding effects. These models learn from single-cell and spatial genomics data to predict cellular and tissue responses to unseen perturbations in silico. I will highlight applications ranging from cell-state discovery to causal modeling of tissue organization and spatial gene regulation. Together, these approaches aim to transform biological discovery by enabling large-scale virtual experimentation at single-cell resolution.
About the speaker
Stathis Megas is Assistant Professor at the Medical University of Vienna, Group Leader at the Center for AI in Medicine, and Key Researcher in the MetAGE Cluster of Excellence. His research focuses on developing generative and causal AI methods for single-cell, spatial, multimodal, and imaging data, with the long-term goal of building Virtual Cells, Virtual Tissues, and Virtual Organs. Prior to joining Vienna, he was a Schmidt Sciences-funded postdoctoral researcher at the University of Cambridge, the Wellcome Sanger Institute, and EMBL-EBI. His academic background spans both artificial intelligence and theoretical physics.