Nenning Karl-Heinz

Karl-Heinz Nenning is a computational neuroscientist at the Computational Imaging Research Lab (CIR) at the Medical University of Vienna, working at the intersection of machine learning, functional MRI, and clinical neuroscience. He holds a PhD in Medical Informatics, Biostatistics and Complex Systems from the Medical University of Vienna, following BSc and MSc degrees in Medical Informatics from the Vienna University of Technology. His central interest is the functional organization of the brain: how it is built, how it varies across individuals and species, and how it breaks down in disorders such as epilepsy and brain tumors. Bridging basic and clinical research, he develops approaches that link mechanistic insight into brain function to questions that matter in the clinic, from predicting cognitive outcomes to supporting treatment decisions. He builds the computational tools this requires, including manifold learning and cross-species alignment methods that establish correspondences across brains and enable a quantitative approach to brain evolution and development. Overall, his research aims to advance the clinical application of neuroimaging, translating what we learn about the brain into better care for it.