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in free-electron-driven X-ray nanophotonics– i.e., modeling the physics of free electrons impinging on nanomaterials like van der Waals crystals, and subsequent coherent X-ray emission and imaging
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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Subproject 1 and device teams in Subproject 3 and other project collaborators. Publish high-impact research in top-tier materials science and applied physics journals. Present research at national
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neural mechanisms, and applying data-driven methods to learn or identify models from empirical data. Notice of Non-Discrimination and Equal Opportunity The University of Delaware does not
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scientific computing, control theory, data science, data driven methods, discrete mathematics, discretization methods, graph algorithms, high-performance computing, integral equations and nonlocal models