Integration Of Machine Learning And Optimization Professors in Global

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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
constrained optimization
stochastic optimization
distributed optimization
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Borzou Rostami
University of Alberta Canada
integration of machine learning and optimization
machine learning applied to real-time decision making
large-scale optimization
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John Jørgensen
Technical University of Denmark Denmark
process optimization
numerical optimization
dynamic optimization
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Merve Bodur
University of Edinburgh United Kingdom
combinatorial optimization
inverse optimization
multiobjective optimization
robust optimization
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Merve Bodur
University of Edinburgh United Kingdom
combinatorial optimization
inverse optimization
multiobjective optimization
robust optimization
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Chaoyue Zhao
University of Washington United States of America
data-driven optimization
robust optimization
stochastic optimization
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Chaoyue Zhao
University of Washington United States of America
data-driven optimization
robust optimization
stochastic optimization
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Yan Li
Texas A&M University United States of America
dynamic optimization
robust optimization
stochastic optimization
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Houra Mahmoudzadeh
University of Waterloo Canada
inverse optimization
robust optimization
large-scale optimization
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Mahdi Mehrtash
Johns Hopkins University United States of America
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global optimization
power system optimization
stochastic optimization
distributed optimization
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Hossein Hashemi Doulabi
Concordia University Canada
robust optimization
stochastic optimization
large-scale optimization
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Xu Zhou
Imperial College London United Kingdom
robust optimization
stochastic optimization
distributed optimization
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Albert Berahas
University of Michigan United States of America
machine learning optimization
constrained optimization
stochastic optimization
distributed optimization
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Shixuan Zhang
Texas A&M University United States of America
integer optimization
robust optimization
stochastic optimization
polynomial optimization
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Wolfgang Lehner
Aalborg University Denmark
optimization algorithms
query optimization
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Kalyanmoy Deb
Michigan State University United States of America
process optimization
computational optimization
hybrid optimization algorithms
multi-objective optimization
meta-modeling optimization
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Conrad Tucker
Carnegie Mellon University United States of America
design optimization
data integration
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Martin Berggren
Umeå University Sweden
numerical optimization
computational design optimization
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Constantine Caramanis
University of Texas at Austin United States of America
adaptable optimization
robust optimization
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Ruth Misener
Imperial College London United Kingdom
computational optimization
optimization models
data-driven optimization
robust optimization
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Daniel Kuhn
École Polytechnique Fédérale de Lausanne Switzerland
data-driven optimization
robust optimization
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