Federal Grant Award Summary

The University of Houston System received a $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program, effective June 15, 2026 through May 31, 2029. The award supports the development of an energy-stable neural basis framework designed to advance physics-informed artificial intelligence methods for modeling complex multiscale porous media flow and transport phenomena. The research deliverables include the creation of operator-aware, energy-consistent residual formulations incorporating expressive neural basis representations and fractional Sobolev boundary treatments to address fundamental limitations in existing machine learning approaches to partial differential equations used in carbon storage, hydrogen containment, and groundwater management applications.

Beyond core research products, the grant incorporates substantial workforce development and dissemination components. The project will produce educational outcomes through graduate and undergraduate student training, mentoring programs, and open-source software development to strengthen the nation's technical workforce in artificial intelligence and computational science. The work advances foundational research at the intersection of computational mathematics, artificial intelligence, and scientific computing, supporting national priorities in AI-enabled scientific discovery and high-performance computing as emphasized under the Mathematical and Physical Sciences program's mandate to strengthen the nation's scientific enterprise.