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Today, companies across a wide range of industries face the challenge of managing increasingly complex stochastic systems, where uncertainty is inherent and data is abundant. These systems arise in
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of stochastic programming problems used in power system operations under uncertainty in conjunction with classical high-performance computing. Interesting directions for this project include, but are not limited
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range of industries face the challenge of managing increasingly complex stochastic systems, where uncertainty is inherent and data is abundant. These systems arise in diverse domains—such as manufacturing
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of this project is to develop techniques that will enable gate-based quantum optimization algorithms to tackle realistic (large-scale, mixed-integer, and constrained) instances of stochastic programming problems