This $180,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences supports the development of a multimodal transformer-based model for time-series prediction and spatiotemporal analysis. The project aims to create algorithms for forecasting time-series, predicting spatial dynamics, and detecting anomalies, which can be applied to data analysis and high-consequence decision-making. The research will address how to utilize contextual information with time series for reliable predictions and consistently incorporate multiple data sources into prediction and anomaly detection models. This award, under the NSF Mathematical and Physical Sciences program (CFDA 47.049), will fund the training of PhD students involved in the research and contribute to advancing the spatial reasoning capabilities of artificial intelligence algorithms. The award period runs from Sept. 1, 2024, to Aug. 31, 2027. No subawards are planned for this grant.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $180.0k | 8/14/24 |