Michael Moor
Assistant Professor at ETH Zürich
Switzerland
Summary
👤
Senior🎓
Top SchoolMichael Moor is an MD PhD and assistant professor at ETH Zurich specializing in medical AI, combining clinical training with rigorous machine learning research. After completing an MD and clinical master's at the University of Basel, he earned a PhD in machine learning for healthcare at ETH Zurich and then applied those methods as a postdoctoral scholar in Stanford CS. Over eight years he has bridged bedside insight and algorithmic development to tackle clinically relevant AI problems, with a focus on translational impact rather than purely methodological work. His career trajectory—clinician, researcher, and now faculty—signals an emphasis on deploying trustworthy, clinically informed AI in real-world healthcare settings. An aspect that sets him apart is hands-on clinical experience alongside deep technical expertise, enabling him to spot pragmatic failure modes that purely technical teams often miss.
8 years of coding experience
PhD, Machine learning in healthcare, PhD, Machine learning in healthcare at ETH ZürichDoctor of Medicine - MD, Doctor of Medicine - MD at University of BaselPostdoctoral research, Computer Science, Postdoctoral research, Computer Science at Stanford University
Stackoverflow
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Github Skills (16)
topological-data-analysis10
autoencoder10
maml9
prediction9
pytorch-geometric8
meta-learning8
biomedical8
learn2learn8
python7
machine-learning7
graph-neural-network5
mining5
pytorch5
time-series4
loss-functions3
Programming languages (2)
Github contributions (5)
BorgwardtLab/Imputing_Signatures
Nov 2019 - Sep 2020
Contributions:402 commits, 12 pushes in 10 months
BorgwardtLab/topological-autoencoders
Apr 2019 - Jan 2022
Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
Contributions:188 commits, 11 pushes, 1 comment in 2 years 9 months
autoencodertopological-data-analysistdapersistent-homology
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