Binary Reverse Engineering Professors in Global

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Merve Bodur
University of Edinburgh United Kingdom
inverse optimization
machine learning
combinatorial optimization
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Merve Bodur
University of Edinburgh United Kingdom
inverse optimization
machine learning
combinatorial optimization
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Nima Anari
Stanford University United States of America
machine learning
randomized algorithms
combinatorial optimization
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Ferenc Huszár
University of Cambridge United Kingdom
machine learning
bayesian machine learning
deep learning
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Garrett Morris
University of Oxford United Kingdom
machine learning
bayesian optimization
deep learning
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Yingfei Wang
University of Washington United States of America
machine learning
bayesian optimization
deep learning
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Geoff Pleiss
University of British Columbia Canada
machine learning
bayesian optimization
probabilistic machine learning
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Daniel Roy
University of Toronto Canada
No active positions
machine learning
deep learning
probabilistic programming
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Nevena Ranković
Tilburg University Netherlands
reverse engineering
machine learning
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Mark Magee
University of Warwick United Kingdom
binary systems
machine learning
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Vicky Kalogera
Northwestern University United States of America
binary systems
machine learning
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Matthias Bickel
ETH Zurich Switzerland
inverse optimization
inverse reinforcement learning
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Thomas Tauris
Aalborg University Denmark
binary systems
x-ray binaries
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Stefan Haufe
Technical University of Berlin Germany
inverse modelling
machine learning
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Prashant Singh
Uppsala University Sweden
inverse modeling
machine learning
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Florian Shkurti
University of Toronto Canada
inverse reinforcement learning
machine learning
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Kimia Ghobadi
Johns Hopkins University United States of America
inverse optimization
mixed-integer programming
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Sergio Cantero Chinchilla
University of Bristol United Kingdom
bayesian inverse problems
machine learning
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Hongkai Zhao
Duke University Singapore
bayesian inverse problems
machine learning
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Andrey Feuerverger
University of Toronto Canada
statistical inverse problems
machine learning
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Kris Kitani
Carnegie Mellon University United States of America
inverse reinforcement learning
deep learning
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