Online Optimization Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
process optimization
computational optimization
multi-objective optimization
hybrid optimization algorithms
meta-modeling optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
stochastic optimization
distributed optimization
constrained optimization
nonlinear optimization
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Albert Berahas
University of Michigan United States of America
machine learning optimization
stochastic optimization
distributed optimization
constrained optimization
nonlinear optimization
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Mahdi Mehrtash
Johns Hopkins University United States of America
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global optimization
stochastic optimization
distributed optimization
power system optimization
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Mark Daskin
University of Michigan United States of America
mathematical optimization
integer optimization
network flows optimization
discrete optimization
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Dick Den Hertog
University of Amsterdam Netherlands
optimization in machine learning
linear optimization
robust optimization
nonlinear optimization
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Eric Kerrigan
Imperial College London United Kingdom
dynamic optimization
multi-objective optimization
control optimization
numerical optimization methods
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
linear optimization
discrete optimization
combinatorial optimization
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Shixuan Zhang
Texas A&M University United States of America
integer optimization
stochastic optimization
robust optimization
polynomial optimization
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Arjan Habraken
Eindhoven University of Technology Belgium
form optimization
topology optimization
section optimization
adaptive optimization
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Merve Bodur
University of Edinburgh United Kingdom
multiobjective optimization
robust optimization
inverse optimization
combinatorial optimization
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Adam Wierman
California Institute of Technology United States of America
online optimization
online algorithms
online learning
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Yashar Pourrahimian
University of Alberta Canada
optimization
mining optimization
data-driven optimization
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Rad Niazadeh
University of Chicago Booth School of Business United States of America
optimization
online algorithms
online learning theory
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John Jørgensen
Technical University of Denmark Denmark
process optimization
numerical optimization
dynamic optimization
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Danial Davarnia
Purdue University United States of America
network optimization
global optimization
discrete optimization
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Siva Maguluri
Georgia Institute of Technology United States of America
optimization
stochastic optimization
distributed optimization
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Nathaniel Bastian
Pennsylvania State University United States of America
optimization
multiple objective optimization
computational stochastic optimization
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Bissan Ghaddar
Western University Canada
optimization models
energy optimization
transportation network optimization
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Nathan Kallus
Cornell University Netherlands
optimization
stochastic optimization
robust optimization
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Sahil Singla
Georgia Institute of Technology United States of America
online algorithms
stochastic optimization
online learning
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