This Project Grant award in the amount of $200,000 from the National Science Foundation (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) will enable the development of a sophisticated statistical framework to quickly and accurately detect anomalies in complex dynamical systems. The project aims to advance the field of dynamical system analysis by creating a fast Bayesian method based on Gaussian processes to estimate time-varying parameters and identify significant changes in physical, biological, and other systems modeled by ordinary and partial differential equations. This new system is anticipated to have significant applications in areas such as disease spread modeling, weather prediction, and threat detection, thereby promoting scientific discoveries, enhancing public health and national defense decision-making. The awarded organization, Georgia Tech Research Corporation, will leverage its extensive expertise in mathematics, statistics, engineering, and data science to complete this project, which also places a strong emphasis on supporting STEM education and diversity.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $200.0k | 7/19/23 |