Statistical Machine Learning Professors in Global

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Nazim Khan
University of Western Australia Australia
statistical computing
stochastic modelling
statistical model selection
statistical clustering
computational statistics
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Berwin Turlach
University of Western Australia Australia
statistical learning
machine learning
statistical computing
computational statistics
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Bryon Aragam
University of Chicago Booth School of Business United States of America
statistical machine learning
statistical learning theory
causal machine learning
probabilistic modeling
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Mehrdad Mahdavi
Pennsylvania State University United States of America
computational statistical machine learning
statistical learning theory
large-scale machine learning
deep learning
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John Lau
University of Western Australia Australia
statistical computing
statistical filtering
statistical clustering
computational statistics
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Nicolas Le Roux
University of Montreal Canada
statistical modeling
machine learning
deep learning
neural networks
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Wenlong Mou
University of Toronto Canada
statistical learning
statistical computing
mathematical statistics
theoretical statistics
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Michael Evans
University of Toronto Canada
statistical computing
statistical inference
mathematical statistics
theoretical statistics
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Gareth Roberts
University of Warwick United Kingdom
statistical inference
stochastic simulation
computational statistics
statistical methodology
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Yee Teh
University of Oxford United Kingdom
machine learning
large scale machine learning
computational statistics
deep learning
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Ismaila Ba
University of Toronto Canada
statistical computing
statistical inference
spatial statistics
theoretical statistics
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Pascal Vincent
University of Montreal Canada
machine learning
statistical models
deep learning
neural networks
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Nathaniel Bastian
Pennsylvania State University United States of America
machine learning
statistical computing
computational stochastic optimization
deep learning
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Xenia Miscouridou
Imperial College London United Kingdom
statistical network modeling
bayesian statistical machine learning
stochastic process modeling
deep learning
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Chris Holmes
University of Oxford United Kingdom
stochastic simulation
statistical genomics
spatial statistics
statistical genetics
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Andrey Feuerverger
University of Toronto Canada
machine learning
statistical theory
mathematical statistics
theoretical statistics
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Houman Owhadi
California Institute of Technology United States of America
machine learning
statistical numerical approximation
multi-scale stochastic analysis
stochastic mechanics
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Houman Owhadi
California Institute of Technology United States of America
machine learning
statistical numerical approximation
multi-scale stochastic analysis
stochastic mechanics
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Markus Pelger
Stanford University United States of America
machine learning
statistical theory
statistical methods
stochastic financial modeling
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Tal Kachman
Radboud University Netherlands
machine learning
statistical physics
financial machine learning
deep learning
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Chinh Lee
Monash University Australia
machine learning
predictive modeling
statistical business analytics
statistical quality control
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