Federal Project Grant Award Summary

Iowa State University of Science and Technology received a $346,686 Project Grant from the National Science Foundation (NSF) Division of Biological Infrastructure under the Biological Sciences program (CFDA 47.074), effective August 1, 2026 through July 31, 2029. This collaborative research project will develop new computational methods and statistical frameworks to enable efficient analysis of high-dimensional (HD) biological data—datasets containing hundreds or thousands of variables per research subject, such as genomic, protein structural, or facial recognition data. The primary deliverable addresses the computational limitations of current analytical methods, which require exponentially increasing computer memory and processing time as data volume increases.

The project will produce two key research outputs: (1) a compressed likelihood strategy that calculates robust lower-dimensional matrix determinants consistent with higher-dimensional estimates, enabling likelihood estimation when variables exceed research observations; and (2) recursive algorithms to further reduce computational burden for HD data analysis. Beyond the core research products, the award supports broader impacts through development of open-source software tools, mentorship and training opportunities for student and researcher development, and organized workshops to disseminate computational techniques to the scientific community. These deliverables directly advance NSF's priorities in artificial intelligence applications and address critical gaps in statistical computation methods for ecology and evolutionary biology research.