Octavian Ganea is a postdoctoral researcher and ML scientist with 11 years of experience embedding geometry into deep learning to accelerate drug and materials discovery. Based at MIT after a PhD from ETH Zürich, he builds models that inject Euclidean symmetries and physical first principles to constrain 3D molecular and material structures, improving accuracy, efficiency, and trust. He also challenged conventional geometric assumptions in representation learning by developing principled Riemannian methods that leverage hyperbolic and elliptic spaces, with implications across robotics, 3D graphics, vision, and NLP. His background includes internships at Google Brain and practical algorithmic work in C++ for protein sequencing, reflecting a blend of theoretical rigor and production-minded engineering.
11 years of coding experience
6 years of employment as a software developer
Master of Science (MSc) Computer Science, Master of Science (MSc) Computer Science at EPFL
Doctor of Sciences Computer Science, Doctor of Sciences Computer Science at ETH Zürich
POLITEHNICA București National University for Science and Technology
High School Diploma, High School Diploma at Tudor Vianu National High School, Bucharest
Source code for the paper "Probabilistic Bag-Of-Hyperlinks Model for Entity Linking" , http://dl.acm.org/citation.cfm?id=2882988
Contributions:24 commits, 1 PR, 24 pushes in 3 years
acmcitationentityentity-linkinglinking
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