Caroline Weis
Director, AI For Science Bei GSK.ai
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolCaroline Weis is a Senior AI/ML Engineer specializing in biomedical AI with nine years of experience bridging cutting-edge research and industry impact at GSK.ai. Currently pursuing a PhD in Machine Learning for Healthcare at ETH Zurich, she builds predictive models for antimicrobial resistance from MALDI-TOF mass spectrometry using topological data analysis, kernel methods and optimal transport. Her work also spans survival analysis on human genotypes and single-cell cancer data, reflecting a strong focus on personalized medicine and translational bioinformatics. At GSK she leads applied ML efforts that bring research-grade methods into production for real-world drug discovery and diagnostics. Known for combining rigorous theory with practical engineering, she keeps actively engaged with time-series EHR methods and graph/kernel research trends to inform her projects. Based in Zurich, she pairs deep academic training with hands-on industry experience to tackle clinically relevant ML problems.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science (B.Sc.) Integrated Life Sciences (Biology, Biophysics, Biomathematics), Bachelor of Science (B.Sc.) Integrated Life Sciences (Biology, Biophysics, Biomathematics) at FAU Erlangen-NürnbergDr. sc. ETH Zurich Machine Learning for Healthcare, Dr. sc. ETH Zurich Machine Learning for Healthcare at ETH Zürich
German, English, French
Github Skills (5)
machine-learning10
python10
preprocessing8
kernel7
machine-learning-models1
Programming languages (2)
Github contributions (5)
BorgwardtLab/maldi_PIKE
Jan 2020 - Apr 2022
Code for 'Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra'
Contributions:8 commits, 2 PRs, 7 pushes in 2 years 2 months
kernel
cvweis/cvweis.github.io
Jun 2023 - May 2024
Contributions:11 pushes, 1 branch in 10 months
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