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Explore structure-preserving learning for high-dimensional Lagrangian and Hamiltonian systems, focusing on reduced-order models in mechanics, robotics, and wave propagation for enhanced stability and predictive accuracy.
Explore AI-driven techniques for predicting heart rhythm disorders using spatio-temporal imaging data, combining fluorescence and ultrasound imaging to overcome diagnostic limitations.
Explore cybersecurity challenges in distributed energy systems and learn techniques for detecting and mitigating cyber attacks using optimization, control theory, and machine learning.
Explore opportunities and challenges of integrating AI into wargaming, enhancing strategic decision-making and scenario analysis for defense and security applications.
Explore quantum information and data science approaches for modeling classical dynamics, focusing on operator-theoretic techniques and their applications in dynamical systems and climate modeling.
Explore homogenized energy theory for solving elasticity problems, addressing limitations in classical continuum mechanics and offering insights into size effects and stress singularities.
Explore advancements in hybridizable discontinuous Galerkin methods for high-order finite element calculations, featuring flexible implementations for diverse PDEs and applications.
Explore advanced radio-frequency wave simulation techniques in hot magnetized plasma, focusing on innovative approaches to construct dielectric operators with all-order finite Larmor radius effects.
Explore recent advancements in MFEM, including GPU optimizations, new mini-apps, and integrations with scientific software libraries for high-order finite element calculations.
Explore high-order phase-space simulations for Boltzmann transport using MFEM's new multidimensional discretization, enhancing fusion energy experiment modeling.
Explore contact constraint enforcement in scientific simulations using Tribol, an open-source library for MFEM. Learn about MPI parallel implementation, Lagrangian methods, and integration with MFEM-based codes.
Explore MFEM's enhanced capabilities through libCEED integration, including support for simplices, mixed meshes, and p-adaptivity. Discover performance gains across various HPC architectures.
Explore scalable design and optimization using MFEM for large-scale scientific simulations. Learn about topology and shape optimization algorithms, gradient-based techniques, and implementation strategies for industrial problems.
Explore cutting-edge finite element research through student presentations on topics like µFEA, entropy stabilization, Maxwell's equations, and thermo-mechanical solves using MFEM.
Explore cutting-edge research in high-order mathematical calculations for scientific simulations through student presentations on neural networks, GPU acceleration, and Monte Carlo methods.
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