Innovations in Data Assimilation: Theory, Algorithms, and Application
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Organizer(s): |
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Adam Larios
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University of Nebraska-Lincoln
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USA
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Jared Whitehead
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Brigham Young University
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USA
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Introduction:
| | This mini-symposium brings together researchers and practitioners to explore the broad landscape of data assimilation, bridging theoretical foundations and practical applications. Theoretical topics include nudging-based approaches, continuous data assimilation, and their link to PDEs, control theory, and error analysis. On the applied side, the symposium will highlight Bayesian and filtering methods such as the ensemble Kalman filter, particle filter, and continuous-in-time formulations like nudging and the ensemble Kalman-Bucy filter, with applications in climate, atmospheric, and engineering systems.
A central aim is to foster connections between data assimilation and related areas, such as machine learning, stochastic modeling, parameter estimation, and optimal control,to promote interdisciplinary collaboration and inspire new research directions. The event will also provide an engaging platform for early-career researchers to exchange ideas and gain exposure to modern methods for complex dynamical systems.
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