Geoffrey Schau
AI Research Scientist Office Of The CTO at Allen Institute
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolGeoffrey Schau is an AI research scientist with 11 years of experience applying computer vision and deep learning to cellular and clinical imaging, currently scaling foundational models of 3D neuroanatomy and cellular organization at the Allen Institute. His work bridges digital pathology, hyperplexed imaging, and single-cell biology, with strengths in self-supervised representation learning, instance segmentation, and designing human–machine partnerships for biomarker discovery. Previously he built production-grade vision systems for tumor organoid screening at Tempus and automated spatial immuno-biomarker detection at Genentech, bringing lab-grade rigor to ML-driven diagnostics. Trained as a biomedical engineer with an MS in electrical engineering and a PhD in biomedical engineering, he combines systems thinking with hands-on algorithm development across multi-modal data integration. Notably, he has transitioned techniques proven on whole-slide histology into larger-scale 3D neuroanatomy models, surfacing biological insight from increasingly complex imaging modalities.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Biomedical Engineering, Doctor of Philosophy - PhD Biomedical Engineering at Oregon Health & Science UniversityMaster of Science - MS Electrical Engineering, Master of Science - MS Electrical Engineering at Portland State UniversityBachelor of Science - BS Biomedical Engineering, Bachelor of Science - BS Biomedical Engineering at Rose-Hulman Institute of Technology
Github Skills (15)
pytorch10
machine-learning10
deep-learning10
tensorflow10
python10
data-science10
autoencoder9
normalization9
jax9
variational-autoencoder9
neural-network8
keras7
image-analysis7
computer-vision6
single-cell-genomics4
Programming languages (2)
Github contributions (5)
schaugf/HEnorm_python
Feb 2019 - Jan 2020
H&E histopathological staining normalization
Contributions:16 commits, 1 PR, 3 pushes in 11 months
normalization
schaugf/ImageVAE
May 2018 - Jul 2022
Variational autoencoder (VAE) for image analysis, built in keras
Contributions:90 commits, 1 PR, 76 pushes in 4 years 2 months
autoencoderimage-analysisdeep-learningcomputer-visionmachine-learning
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