The National Science Foundation (NSF) awarded a $199,940 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Georgia Research Foundation, Inc. (UGA Research Foundation) for the project titled "AMPS: Scalable Graph Models for Anomaly Detection in Large-Scale Smart Grids." The project aims to develop advanced, computationally efficient data-driven algorithms for real-time anomaly detection and diagnosis in smart power grids, which are becoming increasingly complex due to the integration of renewable energy sources and reliance on information technologies. The proposed graph-theoretic methods are designed to accurately identify anomalies in multi-modal grid data, addressing limitations of existing techniques in areas like sensitivity, scalability, and stability. This work is expected to make significant theoretical and practical contributions to enhancing the security and resilience of smart grid systems. No sub-awards are planned under this grant.