About Eliza Rezvanova Eliza Rezvanova Ph.D. Student, Applied Mathematics and Computational Science PDEs numerical methods stochastic processes Stochastic Optimal Control Dynamic programming renewable energy Partially Observed Stochastic Optimal Control Eliza Rezvanova research focuses on developing novel mathematical modeling and numerical frameworks for the continuous-time stochastic optimal control of large-scale coupled power systems. Events Presented Events Aug 2 - Aug 8, 2026 Stochastic Optimal Control with Applications to Renewable Energy and Partially Observed Systems Eliza Rezvanova, Ph.D. Student, Applied Mathematics and Computational Science Aug 6, 15:00 - 17:00 B5 R5209; Zoom Meeting 4569553742 Partially Observed Stochastic Optimal Control Stochastic Optimal Control renewable energy Dynamic programming This thesis develops continuous-time dynamic programming frameworks and shows how dynamic programming and HJB methods can be extended to settings that do not satisfy the classical Markovian and full-observation assumptions through appropriate relaxation and state-reformulation techniques.
Stochastic Optimal Control with Applications to Renewable Energy and Partially Observed Systems Eliza Rezvanova, Ph.D. Student, Applied Mathematics and Computational Science Aug 6, 15:00 - 17:00 B5 R5209; Zoom Meeting 4569553742 Partially Observed Stochastic Optimal Control Stochastic Optimal Control renewable energy Dynamic programming This thesis develops continuous-time dynamic programming frameworks and shows how dynamic programming and HJB methods can be extended to settings that do not satisfy the classical Markovian and full-observation assumptions through appropriate relaxation and state-reformulation techniques.
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