Alexander Mathis, Ph.D.

Alexander Mathis is assistant professor at the Brain Mind Institut of the École Polytechnique Fédérale de Lausanne (EPFL). He works at the intersection of computational neuroscience and machine learning, focusing on trying to understand the statistics of behavior and how the brain creates behavior. He studied pure mathematics at the Ludwig-Maximilians-Universität München, where he also obtained his Ph.D. in computational neuroscience (with Andreas V.M. Herz). During his doctoral work, he developed a theory on how space is represented in the brain. He then was a postdoctoral fellow at Harvard University (with Venkatesh N. Murthy) and the University of Tübingen (with Matthias Bethge), working on a broad range of topics from the sense of smell to computer vision.

Since 2020, Mathis has been assistant professor at EPFL, where his group currently works on theories of proprioception and motor control. Additionally, his group develops machine learning tools for behavioral analysis (e.g. DeepLabCut, hBehaveMAE, WildCLIP) and conversely tries to learn from the brain to solve challenging machine learning problems such as learning motor skills. He has received numerous prizes and fellowships, including the 2024 Robert Bing Prize, 2023 Eric Kandel Young Neuroscientists Prize, 2023 Frontiers of Science Award and a Marie Skłodowska-Curie Postdoctoral Fellowship.