Federal Project Grant Award Summary

The National Science Foundation (NSF), Division of Computing and Communication Foundations, awarded a $200,000 Project Grant to the University of Maryland, College Park on July 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070). This collaborative research initiative focuses on graph-based vector databases, addressing the gap between advances in machine learning and the practical deployment of efficient systems to store and search vector embeddings. Vector embeddings—numerical representations derived from machine learning models—encode critical information about digital media including documents, images, and videos. The project aims to improve algorithms that power vector database systems, making them faster, more reliable, and computationally efficient for organizations with limited cloud infrastructure budgets.

The award supports research that will advance vector database technology through algorithmic optimization, enabling broader adoption of artificial intelligence applications across commercial, scientific, and public sectors. By reducing computational resource requirements, the research will facilitate deployment of vector database systems by small businesses, researchers, and other cost-constrained users who currently lack access to massive computing budgets. The project is scheduled for completion by June 30, 2030, and will be conducted at the University of Maryland's College Park campus in Maryland.