Alexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he 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. In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the 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.
Veuillez noter qu'il ne s'agit pas d'une liste complète des publications de cette personne. Elle inclut uniquement les travaux sémantiquement pertinents. Pour une liste complète, veuillez consulter Infoscience.
Silvestro Micera, Friedhelm Christoph Hummel, Alexander Mathis, Solaiman Shokur, Mahdi Hamidi Rad
Devis Tuia, Alexander Mathis, Valentin Alexandre Guy Gabeff
Olaf Blanke, Alexander Mathis, Merkourios Simos
data.zip ~37 GB when uncompressed. This includes:
cleaned_smooth: pre-processed data from FLAG3D and PCR dataset, the elbow flexion datasets u ...