Project Grant 2617390

Federal Grant Award Summary

The Pennsylvania State University received a $400,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) beginning September 1, 2026 and concluding August 31, 2029. This collaborative research award supports the development of neuro-artificial intelligence (neuro-AI) foundations specifically designed to enable spiking neural networks (SNNs) to efficiently process long-range dependencies and generative tasks in resource-constrained edge computing environments such as unmanned aerial vehicles, robots, wearables, and mobile devices. The research addresses the computational inefficiency challenges associated with deploying large foundation models on edge devices while maintaining latency requirements, bandwidth limitations, and privacy protections.

The project delivers algorithmic innovations and hardware-software co-design solutions that rethink SNNs as state space models, spanning multiple technical thrusts from device design and circuit optimization to machine learning and dynamical systems integration. The research aims to achieve orders of magnitude improvements in power and energy efficiency for data-intensive machine learning workloads while providing additional benefits such as adversarial robustness. This interdisciplinary research initiative serves as a platform for training next-generation researchers and engineers in neuromorphic computing and has far-reaching implications for the semiconductor and artificial intelligence industries seeking to enable on-chip inference capabilities in resource-constrained environments.