Bayesian Model Optimization Professors in Global

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Sharmistha Guha
Texas A&M University United States of America
bayesian high dimensional regression
bayesian object-oriented regression
bayesian causal inference
bayesian nonparametric mixture models
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James Beck
California Institute of Technology United States of America
bayesian updating
computational bayesian statistics
stochastic system modeling
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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
meta-modeling optimization
multi-objective optimization
evolutionary multi-objective optimization
hybrid optimization algorithms
process optimization
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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Mark Borsuk
Duke University Singapore
bayesian network modeling
mathematical modeling
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
bayesian methods
efficient bayesian computation
approximate bayesian methods
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Valen Johnson
Texas A&M University United States of America
bayesian variable selection
bayesian hypothesis testing
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Bilge Atasoy
Delft University of Technology Netherlands
prediction-based optimization
choice-based optimization models
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Ottmar Cronie
University of Gothenburg Sweden
bayesian spatio-temporal modeling
statistical modeling
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Jun Zhang
University of Michigan United States of America
bayesian decision theory
computational modeling
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Spyridon Pougkakiotis
King's College London United Kingdom
stochastic optimisation
large-scale deterministic optimisation
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Retsef Levi
Massachusetts Institute of Technology United States of America
stochastic optimization
combinatorial optimization
optimization
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Siva Maguluri
Georgia Institute of Technology United States of America
stochastic optimization
optimization
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Nathan Kallus
Cornell University Netherlands
stochastic optimization
optimization
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Elad Hazan
Princeton University United States of America
stochastic optimization
optimization
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Edward Cripps
University of Western Australia Australia
bayesian longitudinal analysis
probabilistic modeling
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Nathaniel Bastian
Pennsylvania State University United States of America
computational stochastic optimization
optimization
multiple objective optimization
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Yassine Yaakoubi
Concordia University Canada
machine learning-augmented optimization
large-scale combinatorial optimization
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Alexander Strang
University of California, Berkeley United States of America
hierarchical bayesian inference
optimization
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Michael Wheatland
University of Sydney Australia
bayesian probability
computational modeling
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Teemu Pennanen
King's College London United Kingdom
stochastic optimization
statistical modeling
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