Hannah Spitzer | Helmholtz Munich

Portrait of Dr. Hannah Spitzer, Research Group Leader of the Data Analysis and Machine Learning group at ICB, Computational Health Center

Research Group Leader of Data Analysis and Machine Learning group, ICB

hannah.spitzer@helmholtz-munich.de

“My vision is to connect molecular and imaging data across scales to better understand brain diseases and enable more precise, personalized diagnosis and treatment.”

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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.

Machine Learning

Spatial Omics

Neuroscience

Multimodal Data Integration

Computational Biology

Neurovascular Diseases

Since 2023

2019 - 2023

2015 - 2020

“I am particularly proud of our recent Python-based toolbox for spatial omics analysis, which is widely used by the research community to extract meaningful insights from spatial data.”

A recently developed Python-based toolbox for spatial omics analysis is widely used by the research community to extract meaningful insights from spatial data.

2016 - Springorum-Denkmünze award, for excellent Masters studies
2013 - Schöneborn award, for excellent Bachelors studies
2010 - 2014 - Bildungsfonds scholarship from RWTH Aachen and proRWTH, awarded to students who show promise for excellence in their future studies.

Yang, K. ; Spitzer, H. ; Sterr, M. ; Hrovatin, K. ; de la O, S. ; Zhang, X. ; Setyono, E.S.A. ; Ud-Dean, M. ; Walzthoeni, T. ; Flisikowski, K. ; Flisikowska, T. ; Schnieke, A. ; Scheibner, K. ; Wells, J.M. ; Sneddon, J.B. ; Kessler, B. ; Wolf, E. ; Kemter, E. ; Theis, F.J. ; Lickert, H.

A multimodal cross-species comparison of pancreas development.

Ripart, M. ; Spitzer, H. ; Williams, L.Z.J. ; Walger, L. ; Chen, A. ; Napolitano, A. ; Rossi-Espagnet, C. ; Foldes, S.T. ; Hu, W. ; Mo, J. ; Likeman, M. ; Rüber, T. ; Caligiuri, M.E. ; Gambardella, A. ; Guttler, C. ; Tietze, A. ; Lenge, M. ; Guerrini, R. ; Cohen, N.T. ; Wang, I. ; Kloster, A. ; Pinborg, L.H. ; Hamandi, K. ; Jackson, G. ; Tortora, D. ; Tisdall, M. ; Conde-Blanco, E. ; Pariente, J.C. ; Perez-Enriquez, C. ; Gonzalez-Ortiz, S. ; Mullatti, N. ; Vecchiato, K. ; Liu, Y. ; Kälviäinen, R. ; Sokol, D. ; Shetty, J. ; Sinclair, B. ; Vivash, L. ; Willard, A. ; Winston, G.P. ; Yasuda, C. ; Cendes, F. ; Shinohara, R.T. ; Duncan, J.S. ; Cross, J.H. ; Baldeweg, T. ; Robinson, E.C. ; Iglesias, J.E. ; Adler, S. ; Wagstyl, K. ; Fawaz, A. ; De Benedictis, A. ; De Palma, L. ; Zhang, K. ; Labate, A. ; Barba, C. ; You, X. ; Gaillard, W.D. ; Tang, Y. ; Wang, S. ; Davies, S. ; Semmelroch, M. ; Severino, M. ; Striano, P. ; Chari, A. ; D'Arco, F. ; Mankad, K. ; Bargallo, N. ; Pascual-Diaz, S. ; Delgado-Martinez, I. ; O'Muircheartaigh, J. ; Abela, E. ; Kandasamy, J. ; McLellan, A. ; Desmond, P. ; Lui, E. ; O'Brien, T.J. ; Whitaker, K.

Detection of epileptogenic focal cortical dysplasia using graph neural networks: A MELD Study.

Asani, B. ; Holmberg, O. ; Schiefelbein, J.B. ; Hafner, M. ; Herold, T. ; Spitzer, H. ; Siedlecki, J. ; Kern, C. ; Kortuem, K.U. ; Frishberg, A. ; Theis, F.J. ; Priglinger, S.G.

Evaluation of OCT biomarker changes in treatment-naive neovascular AMD using a deep semantic segmentation algorithm.

Mellor, S. ; Timms, R.C. ; O’Neill, G.C. ; Tierney, T.M. ; Spedden, M.E. ; Brookes, M.J. ; Wagstyl, K. ; Barnes, G.R. ; MELD Project Consortium (Spitzer, H.)

Combining OPM and lesion mapping data for epilepsy surgery planning: A simulation study.

Asani, B. ; Horlava, N. ; Spitzer, H. ; Theis, F.J. ; Priglinger, S. ; Schiefelbein, J.

Predicting OCT-morphological anti-VEGF treatment response in patients with neovascular age-related degeneration using artificial intelligence.

Schiefelbein, J. ; Horlava, N. ; Spitzer, H. ; Theis, F.J. ; Priglinger, S. ; Asani, B.

New OCT based definition of treatment response to anti-VEGF in treatment naive neovascular AMD patients using an Deep Learning Algorithm.

Frishberg, A. ; Milman, N. ; Alpert, A. ; Spitzer, H. ; Asani, B. ; Schiefelbein, J.B. ; Bakin, E. ; Regev-Berman, K. ; Priglinger, S.G. ; Schultze, J.L. ; Theis, F.J. ; Shen-Orr, S.S.

Reconstructing disease dynamics for mechanistic insights and clinical benefit.

Spitzer, H. ; Ripart, M. ; Fawaz, A. ; Williams, L.Z.J. ; Robinson, E.C. ; Iglesias, J.E. ; Adler, S. ; Wagstyl, K.

Robust and Generalisable Segmentation of Subtle Epilepsy-Causing Lesions: A Graph Convolutional Approach.

Spitzer, H. ; Berry, S. ; Donoghoe, M. ; Pelkmans, L. ; Theis, F.J.

Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps.

Spitzer, H. ; Sterr, M. ; Hrovatin, K. ; Böttcher, A. ; Theis, F.J. ; Lickert, H. ; de la O, S. ; Kemter, E. ; Sneddon, J. ; Wolf, E.

Single-cell multiomics cross-species comparison of pancreas development.

Dr. Hannah Spitzer

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Academic Career and Research Areas

Fields of Work and Expertise

Professional Background

Junior research group leader at Institute of Stroke and Dementia Research, LMU, and associated research group leader at Helmholtz Munich

Postdoctoral researcher in the group of Fabian Theis at Helmholtz Munich

PhD in Computer Science at Heinrich-Heine University Düsseldorf, Germany and Research Center Jülich, working on automatic analysis of cortical areas in whole-brain histological sections.

Impact

Honors and Awards

Recent Publications

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