This $349,880 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support research at Case Western Reserve University (CWRU) to advance Bayesian hierarchical models for inverse problems. The project aims to develop fast and robust computational methods, known as inverse solvers, that can leverage qualitative properties of unknown factors and provide uncertainty measures for solutions. The research will focus on applying these Bayesian inverse solvers to a range of important real-world applications, including functional MRI, stroke monitoring, biomechanics, linguistics studies, and investment portfolio planning. The innovative combination of matrix-free techniques with Bayesian and data science methods is expected to produce algorithms that are fast, yield better solutions, and are more energy-efficient than approaches based on machine learning and neural networks. This 3-year project, with a start date of July 1, 2025, has the potential to advance research in biotechnology, health sciences, and artificial intelligence.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $349.9k | 6/11/25 |