An Intro to Machine Learning for Biomedical Scientists
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guadalupe gonzalez
guadalupe gonzalez
I joined Genentech/Roche in February 2023, after completing a PhD on graph deep learning for lead discovery advised by Michael Bronstein and Kirill Veselkov at Imperial College London. I am part of the Frontier Research team at Prescient/MLDD in Genentech Research and Early Development (gRED).
My expertise lies at the intersection of graph deep learning and causal inference and my focus is on (causal) graph deep learning for drug discovery/design, from the small-scale (e.g., proteins) to the large-scale (e.g., patient data) systems. I am particularly passionate about applying my knowledge to women’s health to catalyze breakthroughs in women-specific conditions such as endometriosis and preeclampsia.
Senior ML Scientist II
Prescient Design, Genentech
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