Dr. Hannah Spitzer

Hannah Spitzer is a computer scientist working at the intersection of machine learning, computational biology, and neuroscience. She studied Computer Science at RWTH Aachen University and completed her PhD at Heinrich Heine University Düsseldorf in collaboration with Forschungszentrum Jülich. In her doctoral work, she developed deep learning methods for the automatic analysis of cortical areas in whole-brain histological sections, laying the foundation for her interest in extracting meaningful information from biomedical image data.

As a postdoctoral researcher at the Institute of Computational Biology at Helmholtz Munich in the group of Fabian Theis, she expanded her research towards integrating imaging with molecular data. During that time, she developed toolboxes to analyse spatial omics data at cellular and subcellular resolution. In 2023, she joined the Institute of Stroke and Dementia Research at LMU to establish her own group while remaining associated at the Computational Health Center at Helmholtz Munich.

Her research focuses on developing machine learning methods to analyse and integrate multimodal and multiscale brain datasets, including single-cell omics, spatial omics, histology, and neuroimaging. By combining advances from computational biology and computer vision, her work aims to improve our understanding of brain disease and support more precise, personalised diagnosis and treatment. A central feature of her research is its close connection to application: through collaborations with biologists, medical researchers, and clinicians, she develops methods that are both innovative and practically useful.