Theoretical Machine Learning Professors in Global

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Navid Azizan
Massachusetts Institute of Technology United States of America
machine learning
scientific machine learning
trustworthy machine learning
mathematical optimization
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Mats Granath
University of Gothenburg Sweden
deep machine learning
quantum machine learning
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Vincenzo Lipardi
Maastricht University Netherlands
quantum machine learning
evolutionary algorithms
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Chris Eliasmith
University of Waterloo Canada
theoretical neuroscience
neural networks
large-scale neural modelling
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Cheng Ouyang
University of Oxford United Kingdom
trustworthy machine learning
multimodal machine learning
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Flora Salim
University of New South Wales Australia
trustworthy machine learning
multimodal machine learning
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Huan Lei
Michigan State University United States of America
scientific machine learning
stochastic simulations
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Atul Prakash
University of Michigan United States of America
trustworthy machine learning
adversarial machine learning
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Magnus Röding
Chalmers University of Technology Sweden
machine learning
statistical modeling
stochastic modeling
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Yiming Ying
University of Sydney Australia
machine learning
statistical learning theory
optimisation in machine learning
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Luke Miller
Radboud University Netherlands
machine learning
computational modeling
neural network modeling
neural computations
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Huan Lei
Michigan State University United States of America
scientific machine-learning
stochastic simulations
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Susie Rao
ETH Zurich Switzerland
multimodal machine learning
pattern mining
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Arpan Mukhopadhyay
University of Warwick United Kingdom
stochastic modeling
randomized algorithms
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Sijing Zhou
University of Melbourne Australia
machine learning
statistical modeling
large-scale data mining
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Chris Cahill
Michigan State University United States of America
bayesian modeling
hierarchical modeling
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Patrizio Mariani
Technical University of Denmark Denmark
numerical modelling
theoretical ecology
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Mark Daskin
University of Michigan United States of America
mathematical optimization
math modeling
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Teddy Groves
Technical University of Denmark Denmark
computational kinetic modeling
quantitative modeling
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Christopher Musco
New York University Tandon School of Engineering United States of America
theory of algorithms
randomized algorithms
scalable machine learning
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Sergio Chayet
University of Chicago United States of America
game-theoretic models
stochastic models
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