Hannah Spitzer
Principal Investigator For Biomedical Machine Learning
Munich, Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolHannah Spitzer is a Principal Investigator in biomedical machine learning based in Munich with a decade of experience developing multimodal ML methods that fuse histology, spatial and single-cell omics, and neuroimaging to advance brain research and personalized treatments. She leads a data analysis group at LMU Klinikum and Helmholtz Munich, translating cutting-edge supervised, self-supervised and unsupervised representation learning into tools clinicians and wet-lab researchers can use. Her postdoctoral work produced interpretable deep learning models for lesion detection, disease progression forecasting, and subcellular multiplexed image analysis, and contributed to multiple open-source Python packages now used in clinical research. Trained as a computer scientist with a PhD-level research background in high-resolution histological segmentation and 3D reconstruction, she combines systems-level engineering—HPC pipelines and large-image workflows—with biological insight to reveal cytoarchitectural variability. Notably, she has a track record of building methods that move from algorithm to hospital deployment through close interdisciplinary collaboration.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at RWTH Aachen University
Github Skills (29)
image-analysis10
scales10
high-resolution10
single-cell-genomics10
python10
data-science10
spatial-transcriptomics10
machine-learning10
spatial-analysis10
transcriptomics10
single-cell-analysis10
bioinformatics10
spatial10
data-visualization10
scanpy10
Programming languages (3)
Github contributions (5)
theislab/campa
Oct 2021 - Nov 2022
Conditional Autoencoders for Multiplexed Pixel Analysis
Contributions:2 releases, 159 commits, 7 PRs in 1 year 1 month
autoencodersconditionalpythonpixel
theislab/squidpy_reproducibility
Jan 2021 - Jul 2021
Contributions:2 reviews, 17 commits, 2 PRs in 6 months
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