Randomized Optimization Professors in Global

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Albert Berahas
University of Michigan United States of America
stochastic optimization
machine learning optimization
constrained 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
machine learning
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Mahdi Mehrtash
Johns Hopkins University United States of America
No active positions
stochastic optimization
distributed optimization
global optimization
power system optimization
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Yassine Yaakoubi
Concordia University Canada
machine learning-augmented optimization
large-scale combinatorial optimization
stochastic programming
supply value chain optimization
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Siva Maguluri
Georgia Institute of Technology United States of America
stochastic optimization
optimization
distributed optimization
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Reem Khir
Purdue University United States of America
optimization
robust stochastic optimization
constrained optimization
machine learning
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Nathaniel Bastian
Pennsylvania State University United States of America
optimization
computational stochastic optimization
multiple objective optimization
machine learning
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Chuan He
Linköping University Sweden
large-scale optimization
continuous optimization
decentralized optimization
machine learning
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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
process optimization
hybrid optimization algorithms
multi-objective optimization
evolutionary multi-objective optimization
machine learning
meta-modeling optimization
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John Chinneck
Carleton University Canada
optimization
nonlinear optimization
feasibility optimization
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Manuel Lopez-ibanez
University of Manchester United Kingdom
optimisation
combinatorial optimisation
multi-objective optimisation
machine learning
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Xin Fei
University of Edinburgh United Kingdom
optimization
stochastic programming
transportation logistics optimization
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Quan Nguyen
University of Southern California United States of America
control optimization
trajectory optimization
real-time optimization-based control
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Merve Bodur
University of Edinburgh United Kingdom
robust optimization
combinatorial optimization
multiobjective optimization
inverse optimization
machine learning
stochastic programming
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Merve Bodur
University of Edinburgh United Kingdom
robust optimization
combinatorial optimization
multiobjective optimization
inverse optimization
machine learning
stochastic programming
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Gregory Sorkin
London School of Economics and Political Science United Kingdom
randomized optimization
optimization
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Retsef Levi
Massachusetts Institute of Technology United States of America
stochastic optimization
optimization
combinatorial optimization
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Nathan Kallus
Cornell University Netherlands
stochastic optimization
optimization
robust optimization
machine learning
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Elad Hazan
Princeton University United States of America
stochastic optimization
optimization
machine learning
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Johannes Royset
University of Southern California United States of America
stochastic optimization
deterministic optimization
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Johannes Royset
University of Southern California United States of America
stochastic optimization
deterministic optimization
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