Stochastic Generation Scheduling Professors in Global

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J Shanthikumar
Purdue University United States of America
stochastic processes modeling
sequencing
scheduling
production system modeling
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Mircea Grigoriu
Cornell University Netherlands
stochastic calculus
stochastic differential equations
stochastic partial differential equations
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Bryon Aragam
University of Chicago Booth School of Business United States of America
statistical machine learning
deep generative models
statistical learning theory
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Mi Park
University of British Columbia Canada
statistical machine learning
generative ai
theoretical machine learning
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Nazim Khan
University of Western Australia Australia
stochastic modelling
statistical computing
statistical clustering
time series modelling
statistical model selection
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Daniel Roy
University of Toronto Canada
No active positions
sequential decision making
machine learning
probabilistic programming
statistical learning theory
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Sudipto Banerjee
University of California Los Angeles United States of America
stochastic processes
statistical machine learning
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Asaf Cohen
University of Michigan United States of America
stochastic processes
stochastic control problems
machine learning
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David Landriault
University of Waterloo Canada
stochastic modelling
stochastic processes
stochastic control problems
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Haoyang Cao
Johns Hopkins University United States of America
stochastic controls
stochastic differential games
generative models
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James Norris
University of Cambridge United Kingdom
stochastic processes
statistical modeling
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Gareth Roberts
University of Warwick United Kingdom
stochastic simulation
stochastic processes
stochastic differential equations
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Frank Van Der Meulen
Vrije Universiteit Amsterdam Netherlands
stochastic processes
stochastic differential equations
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Khader Khadraoui
Laval University Canada
stochastic processes
stochastic differential equations
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Gareth Roberts
University of Warwick United Kingdom
stochastic simulation
stochastic processes
stochastic differential equations
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Markus Riedle
King's College London United Kingdom
stochastic processes
stochastic analysis
stochastic differential equations
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Paul Jenkins
University of Warwick United Kingdom
stochastic processes
machine learning
statistical genetics
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Sabin Lessard
Université de Montréal Canada
stochastic processes
statistical genetics
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Hua Zhou
University of California Los Angeles United States of America
stochastic processes
machine learning
statistical genetics
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Pavel Gapeev
London School of Economics United Kingdom
stochastic analysis
stochastic games
stochastic control problems
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Mohsen Zayernouri
Michigan State University United States of America
stochastic processes
predictive simulation
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