Federal Grant Award Summary

The University of Central Florida Board of Trustees received a $199,852 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), effective July 1, 2026, through June 30, 2029. This collaborative research project develops an efficient and robust algorithmic framework for large-scale tensor data analysis, addressing the challenge of extracting reliable information from multidimensional datasets that are often large, high-dimensional, noisy, and partially corrupted. The deliverables include new scalable and provably robust tensor algorithms with rigorous theoretical foundations, focusing on mode-wise sampling methods, low-rank tensor representations, randomized numerical techniques, and non-convex optimization algorithms for recovering useful information from corrupted or incomplete data.

The project produces mathematical guarantees for the proposed methodologies, including convergence analysis, perturbation bounds, and sampling reliability assessments, while advancing computational efficiency and robustness in high-dimensional settings. Research outcomes support national priorities in artificial intelligence and advanced computing with potential applications to medical imaging and national security. The award also supports educational objectives through training of two graduate students and research opportunities for undergraduate students in computational mathematics, optimization, and data science, along with outreach activities designed to promote STEM participation and foster pathways to research and technical careers.