Alexander Mathis is an Assistant Professor at the École polytechnique fédérale de Lausanne. He grew up in Austria and studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. He also spent an exchange year at the Universitat Autònoma de Barcelona. Fascinated by cryptography and computing, he got interested in how the brain functions and pursued a PhD with Prof. Andreas Herz in Munich. He was part of the Graduate School for Systemic Neuroscience and worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
He is interested in elucidating how the brain gives rise to adaptive behavior. One of his major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.