Statutory Professor (Chair) Of Statistical Science
England, United Kingdom
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Summary
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Patrick Rebeschini is a Statutory Professor and Chair of Statistical Science at the University of Oxford, combining nine years of academic leadership with deep technical expertise in high-dimensional probability, statistics, and optimization for machine learning. He researches and designs algorithms that are both computationally and statistically efficient, bridging theoretical foundations with practical ML methods. His trajectory—PhD and MA from Princeton and a background in theoretical physics from Padua—gives him a rare cross-disciplinary lens on probabilistic modeling and algorithmic complexity. He has progressed through roles at Oxford, Yale and Princeton, mentoring students and shaping curricula while maintaining an active research agenda. Notably, his work emphasizes fundamental limits in high-dimensional settings, informing principled algorithm design rather than purely empirical modeling.
9 years of coding experience
11 years of employment as a software developer
Master of Science (M.S.), Theoretical Physics, Master of Science (M.S.), Theoretical Physics at Università degli Studi di Padova
Imperial College International Diploma, Physics, Imperial College International Diploma, Physics at Imperial College London
Doctor of Philosophy (Ph.D.), Probability Theory and Statistics, Doctor of Philosophy (Ph.D.), Probability Theory and Statistics at Princeton University
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Patrick Rebeschini - Statutory Professor (Chair) Of Statistical Science