Ai Enhanced Optimization Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
process optimization
hybrid optimization algorithms
multi-objective optimization
machine learning
evolutionary multi-objective optimization
meta-modeling 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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Nathaniel Bastian
Pennsylvania State University United States of America
optimization
computational stochastic optimization
machine learning
multiple objective optimization
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Siva Maguluri
Georgia Institute of Technology United States of America
stochastic optimization
optimization
distributed optimization
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Nathan Kallus
Cornell University Netherlands
stochastic optimization
optimization
machine learning
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Elad Hazan
Princeton University United States of America
stochastic optimization
optimization
machine learning
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Zhe Zhang
Purdue University United States of America
stochastic optimization
distributed optimization
machine learning
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Jaroslav Fowkes
University of Oxford United Kingdom
optimization
bayesian optimization
machine learning
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Bistra Dilkina
University of Southern California United States of America
stochastic optimization
discrete optimization
machine learning
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Bistra Dilkina
University of Southern California United States of America
stochastic optimization
combinatorial optimization
discrete optimization
machine learning
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Viswanath Nagarajan
University of Michigan United States of America
stochastic optimization
discrete optimization
machine learning
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Mark Van Oyen
University of Michigan United States of America
stochastic optimization
machine learning
online stochastic optimization
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Fengqi You
Cornell University Netherlands
optimization algorithms
machine learning
supply chain optimization
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Can Li
Purdue University United States of America
generative ai for optimization models
large-scale optimization
machine learning
optimization-inspired neural networks
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Wolfgang Lehner
Aalborg University Denmark
optimization algorithms
machine learning
query optimization
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Navish Kumar
University of Basel Switzerland
optimization
machine learning
riemannian optimization
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Jonathan Shapiro
University of Manchester United Kingdom
optimization
machine learning
evolutionary algorithms
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Garrett Morris
University of Oxford United Kingdom
bayesian optimization
machine learning
generative ai
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Basem Suleiman
University of New South Wales Australia
applied ai
machine learning
generative ai
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Manuel Lopez-ibanez
University of Manchester United Kingdom
combinatorial optimisation
machine learning
multi-objective optimisation
optimisation
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Ignacio Grossmann
Carnegie Mellon University United States of America
continuous optimization
discrete optimization
supply chain optimization
energy systems optimization
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