Project Grant 2311597

The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $200,000 Project Grant to Temple University to develop transformative machine learning and data analytics technologies for enabling AI-based applications on resource-constrained edge computing devices. The project aims to address gaps between the complexity of data and the limited computing resources on edge devices, as well as the need for robust predictive models across heterogeneous edge environments. Key objectives include designing deep neural network acceleration techniques for fine-grained data analytics on commercial off-the-shelf edge devices, developing novel multivariate data analytic models to characterize high-dimensional sensing data, and creating environment-transferable features and models to enable easy deployment of AI-enabled applications. The project, which runs from September 1, 2023 to August 31, 2026, seeks to integrate the research with graduate and undergraduate curricula and promote female engineering student involvement. No sub-awards are planned for this Project Grant, which falls under the NSF's Computer and Information Science and Engineering (CISE) program (CFDA 47.070).