Federal Grant Award Summary

The University of North Carolina at Chapel Hill received a $250,000 Project Grant award from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for the period of July 1, 2026, through June 30, 2029. The project develops theoretical foundations, methodological approaches, and computational tools for modeling time-dependent systems characterized by unknown heterogeneity across multiple subjects. This research addresses a critical gap in analyzing high-dimensional, multivariate time series data arising from diverse domains including precision medicine, computational psychiatry, neuroscience, economics, and machine learning, where meaningful between-subject heterogeneity is inherent to biological, behavioral, and economic systems.

The deliverables include the creation of a unified statistical and machine learning framework capable of handling complex multivariate time series collected from heterogeneous subjects, with applications to sensor-based physiological measurements, health tracking data, and macro-level economic indicators. The project incorporates broader impacts activities focused on education and training of undergraduate and graduate students, contributing to the development of the next generation of researchers in this interdisciplinary area of statistics and computational methodology.