The National Science Foundation (NSF) awarded a $484,822 Project Grant through its Computer and Information Science and Engineering (CFDA #47.070) program to the University of Chicago. This 5-year grant, effective July 1, 2023, supports research into characterizing the properties, reliability, and sensitivity of graph neural networks (GNNs) and advancing the theoretical understanding of statistical properties in graph estimators. The goal is to transform GNNs from black-box models into explainable, trustworthy, and reliable analysis pipelines for learning representations from relational data. The resulting algorithms will be deployed in diverse applications, and efforts will be made to promote the utilization of these methods through open-source software, new graduate courses, and collaborations with community colleges.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $484.8k | 6/26/23 |