This project develops a deep generative graph learning framework to forecast behind-the-meter solar power generation and load.

This project focuses on characterizing smart meter data using advanced deep learning methods to effectively detect electricity theft.

AI-based embedding calculation for automated and scalable detection of incipient phenomena that can lead to future power disruptions.

Scalable creation of labels that enrich large volumes of multivariate time series data making efficient use of domain knowledge information.