Heuristic Optimization Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
hybrid optimization algorithms
computational optimization
process optimization
multi-objective optimization
meta-modeling optimization
evolutionary multi-objective optimization
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Albert Berahas
University of Michigan United States of America
stochastic optimization
machine learning optimization
constrained optimization
nonlinear optimization
distributed optimization
derivative-free optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
stochastic optimization
optimization algorithms
constrained optimization
nonlinear optimization
distributed optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
combinatorial optimization
nonlinear optimization
stochastic mathematical programming
convex optimization
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Merve Bodur
University of Edinburgh United Kingdom
combinatorial optimization
robust optimization
stochastic programming
multiobjective optimization
inverse 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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Marco Chiarandini
University of Southern Denmark Denmark
heuristics
optimization algorithms
combinatorial optimization
continuous optimization theory
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Shixuan Zhang
Texas A&M University United States of America
stochastic optimization
polynomial optimization
integer optimization
robust optimization
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Mahdi Mehrtash
Johns Hopkins University United States of America
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stochastic optimization
global optimization
distributed optimization
power system optimization
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Manuel Lopez-ibanez
University of Manchester United Kingdom
heuristics
optimisation
combinatorial optimisation
multi-objective optimisation
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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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Eric Kerrigan
Imperial College London United Kingdom
dynamic optimization
control optimization
multi-objective optimization
numerical optimization methods
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Dick Den Hertog
University of Amsterdam Netherlands
linear optimization
optimization in machine learning
robust optimization
nonlinear optimization
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Katya Scheinberg
Georgia Institute of Technology United States of America
optimization
continuous optimization
convex optimization
derivative-free optimization
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Yaoliang Yu
University of Waterloo Canada
optimization algorithms
robust stochastic optimization
non-convex optimization
convex optimization
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Jelena Diakonikolas
University of Wisconsin–Madison United States of America
large-scale optimization
first-order optimization algorithms
non-convex optimization
convex optimization
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Michael Patriksson
Chalmers University of Technology Sweden
combinatorial optimization
nonlinear optimization
non-differentiable optimization
convex optimization
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Mehrdad Mahdavi
Pennsylvania State University United States of America
large-scale optimization
distributed optimization
non-convex optimization
convex optimization
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Brad Calder
University of California, San Diego United States of America
memory hierarchy placement optimizations
value-based optimization
compiler optimizations
dynamic compilation optimization
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Somayeh Sojoudi
University of California, Berkeley United States of America
optimization theory
low-rank optimization
non-convex optimization
conic optimization
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Nathan Kallus
Cornell University Netherlands
stochastic optimization
optimization
robust optimization
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