Federal Project Grant Award Summary

Iowa State University of Science and Technology received a $699,774 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070: Computer and Information Science and Engineering) effective October 1, 2026, with completion scheduled for September 30, 2030. The primary deliverable is the development of fast, communication-efficient distributed algorithms for large-scale computational imaging and artificial intelligence (AI) applications. Specifically, the research focuses on two classes of robust low-rank matrix and tensor learning problems: (1) low-rank plus sparse matrix recovery from missing or undersampled data, and (2) low-rank recovery from shuffled, column-wise undersampled measurements. These algorithmic advances target practical applications including dynamic magnetic resonance imaging, image and video compression, object detection and tracking for autonomous vehicles, multi-target tracking in robotics, and efficient adaptation of large language models for specialized use cases.

In addition to core research deliverables, the award supports education and workforce development through expansion of the CyMath K-12 mathematics program. The project will transform CyMath into a multi-tier mathematics mentoring program serving K-12 students, undergraduate tutors, and graduate student mentors, while conducting pilot evaluations of the program's educational impact. This integrated approach combines foundational algorithmic research with educational outreach, positioning the work to advance both distributed learning theory and practical implementation in near-real-time medical imaging and reliable AI systems.