Stochastic Optimization Problems Professors in Global

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Albert Berahas
University of Michigan United States of America
stochastic optimization
constrained optimization
machine learning optimization
distributed optimization
nonlinear optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
stochastic optimization
optimization algorithms
constrained optimization
distributed optimization
nonlinear optimization
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Harold Kushner
Brown University United States of America
stochastic networks
stochastic systems theory
stochastic control
complex stochastic systems
optimization methods
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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
hybrid optimization algorithms
multi-objective optimization
process optimization
meta-modeling optimization
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Jose Figueroa-lopez
Purdue University United States of America
stochastic analysis
stochastic processes
portfolio optimization problems
stochastic control
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Shixuan Zhang
Texas A&M University United States of America
stochastic optimization
polynomial optimization
robust optimization
integer optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
stochastic mathematical programming
combinatorial optimization
nonlinear optimization
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
linear optimization
combinatorial optimization
discrete optimization
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Bartolomeo Stellato
Princeton University United States of America
mathematical optimization
large scale optimization
differentiable optimization
real-time embedded optimization
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Mircea Grigoriu
Cornell University Netherlands
stochastic calculus
stochastic differential equations
numerical methods for solving stochastic problems
stochastic partial differential equations
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Merve Bodur
University of Edinburgh United Kingdom
stochastic programming
combinatorial optimization
multiobjective optimization
robust optimization
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Dick Den Hertog
University of Amsterdam Netherlands
linear optimization
optimization in machine learning
nonlinear optimization
robust optimization
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Eric Kerrigan
Imperial College London United Kingdom
multi-objective optimization
numerical optimization methods
dynamic optimization
control optimization
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Pierre Flener
Uppsala University Sweden
combinatorial optimization
stochastic local search
discrete optimization
constraint solving
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David Landriault
University of Waterloo Canada
stochastic control problems
stochastic modelling
stochastic processes
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Richard Serfozo
Georgia Institute of Technology United States of America
optimization of stochastic systems
stochastic networks
stochastic processes
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Pavel Gapeev
London School of Economics United Kingdom
stochastic control problems
stochastic analysis
stochastic games
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James Spall
Johns Hopkins University United States of America
stochastic optimization
stochastic systems
optimization theory
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Hossein Hashemi Doulabi
Concordia University Canada
stochastic optimization
large-scale optimization
robust optimization
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Ruiwei Jiang
University of Michigan United States of America
stochastic optimization
data-enabled stochastic optimization
discrete optimization
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Alexandre Jacquillat
Massachusetts Institute of Technology United States of America
stochastic optimization
large-scale optimization
integer optimization
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