Inverse Optimization Professors in Global

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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
constrained optimization
nonlinear optimization
stochastic optimization
distributed optimization
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Albert Berahas
University of Michigan United States of America
constrained optimization
nonlinear optimization
machine learning optimization
stochastic optimization
distributed optimization
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Merve Bodur
University of Edinburgh United Kingdom
inverse optimization
combinatorial optimization
robust optimization
multiobjective optimization
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Venkat Chandrasekaran
California Institute of Technology United States of America
inverse problems
optimization
convex optimization
combinatorial optimization
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Venkat Chandrasekaran
California Institute of Technology United States of America
inverse problems
optimization
convex optimization
combinatorial optimization
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Venkat Chandrasekaran
California Institute of Technology United States of America
inverse problems
optimization
convex optimization
combinatorial optimization
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Venkat Chandrasekaran
California Institute of Technology United States of America
inverse problems
optimization
convex optimization
combinatorial optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
nonlinear optimization
convex optimization
combinatorial 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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Marina Epelman
University of Michigan United States of America
mathematical optimization
integer optimization
discrete optimization
optimization under uncertainty
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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
process optimization
multi-objective optimization
hybrid optimization algorithms
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Dick Den Hertog
University of Amsterdam Netherlands
optimization in machine learning
linear optimization
nonlinear optimization
robust 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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Eric Kerrigan
Imperial College London United Kingdom
control optimization
dynamic optimization
multi-objective optimization
numerical optimization methods
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Shixuan Zhang
Texas A&M University United States of America
integer optimization
polynomial optimization
robust optimization
stochastic optimization
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John Chinneck
Carleton University Canada
optimization
nonlinear optimization
mixed integer optimization
feasibility optimization
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Mehrdad Mahdavi
Pennsylvania State University United States of America
non-convex optimization
convex optimization
large-scale optimization
distributed optimization
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Somayeh Sojoudi
University of California, Berkeley United States of America
non-convex optimization
optimization theory
conic optimization
low-rank 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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Michael Patriksson
Chalmers University of Technology Sweden
nonlinear optimization
convex optimization
combinatorial optimization
non-differentiable optimization
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Houra Mahmoudzadeh
University of Waterloo Canada
inverse optimization
large-scale optimization
robust optimization
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