👋 I recently joined GenBio.ai as a research scientist. Before that, I completed my PhD in machine learning and computational biology under the joint supervision of Laura Cantini at Institut Pasteur and Gabriel Peyré at ENS PSL. My research focused on leveraging optimal transport techniques for analyzing single-cell multiomics data, bridging the fields of machine learning and genomics.
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gjhuizing (Geert-Jan Huizing) · GitHub
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🎓
Defended my Ph.D.! Open to new roles
Geert-Jan Huizing gjhuizing
🎓
Defended my Ph.D.! Open to new roles
Research scientist @ GenBio.ai
-
GenBio.ai
- Paris, France
-
01:02
(UTC +02:00) - https://gjhuizing.github.io/
- @gjhuizing
- in/gjhuizing
Organizations
Pinned Loading
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cantinilab/stories
cantinilab/stories PublicLearning cell fate landscapes from spatial transcriptomics using Fused Gromov-Wasserstein
Python 13
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cantinilab/Mowgli
cantinilab/Mowgli PublicSingle-cell multi-omics integration using Optimal Transport
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CSDUlm/wsingular
CSDUlm/wsingular PublicPython package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".
Python 10
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cantinilab/OT-scOmics
cantinilab/OT-scOmics PublicThis Python package will allow you to replicate the experiments from our research on applying Optimal Transport as a similarity metric in between single-cell omics data.
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