Biography

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. We work at the intersection of computational neuroscience and machine learning. Ultimately, we are interested in reverse engineering the algorithms of the brain, in order to figure out how the brain works and to build better artificial intelligence systems. 
We develop machine learning tools for behavioral (e.g. DeepLabCut, AmadeusGPT, DLC2action) and neural data analysis and conversely try to learn from the brain to solve challenging machine learning problems such as learning motor skills.