Project Grant N629092512036

This $500,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports a collaborative research effort between Yale University and its partners to develop energy-efficient algorithms and hardware for spike-based edge computing. The project aims to integrate spiking neural networks (SNNs), a brain-inspired computing paradigm, with modern integrated circuits to enable practical deployment of neuromorphic...

This $255,999 National Science Foundation award under the Technology, Innovation, and Partnerships program will support Zenoleap LLC's development of novel superconducting neuromorphic computing circuits. The awardee will design, fabricate, and characterize atomic-tunable memristors and superconducting quantum interference device neurons to enable true biological brain-inspired deep learning network algorithms. This superconducting neuromorphic circuit aims to significantly improve energy...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant, award ID 2403723, provides $500,000.00 to Cornell University to develop novel algorithms and hardware designs for energy-efficient, memory-optimized spiking neural network (SNN) systems on edge computing devices. The project aims to advance the practical deployment of neuromorphic computing for applications like drones, autonomous robots, portable medical devices, and wearable...

This $329,099 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to uncover the principles of robust intelligence by disentangling the functional architecture of the brain. The primary objectives are to: 1) Identify the systems underlying navigation using whole-brain recordings of zebrafish larvae, and 2) Determine the subsystems underlying visual decision-making in multi-electrode recordings of...

The National Science Foundation awarded a $599,304 three-year Project Grant to the University of California, Santa Barbara under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support the development of novel methods and hardware architectures for optimization and acceleration of spiking neural networks. Key products will include algorithms, software design tools, and field-programmable gate array hardware architectures and...

This $2 million Project Grant from the National Science Foundation's Office of Emerging Frontiers and Multidisciplinary Activities will fund research at Cornell University from October 2022 through September 2026 under the federal Engineering program (CFDA 47.041). The grant aims to advance neuromorphic computing by developing algorithms and computational models inspired by biological neural circuits. Researchers will extract principles from neuroscience to design a neural network...

This $638,022 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of an indium-oxide-based neural computing platform. The goal is to create a more reliable, energy-efficient, and scalable platform for running large language models and other AI workloads at the edge. Key objectives include: Advancing the scientific understanding of oxide semiconductors through...

The National Science Foundation (NSF) Office of Emerging Frontiers and Multidisciplinary Activities awarded a $1,999,968 Project Grant to the University of California, Santa Barbara (UCSB) under the NSF Engineering (CFDA 47.041) program. This grant aims to develop scalable algorithms and hardware for human-brain-scale neuromorphic systems with practical learning capabilities. The key objectives are to create hardware-friendly local learning algorithms, a framework for continual online...

This $250,000 Project Grant award from the National Science Foundation's Engineering (CFDA 47.041) program to The Pennsylvania State University (Penn State) supports a collaborative research project on "Spintronics Enabled Stochastic Spiking Neural Networks with Temporal Information Encoding". The goal is to advance neuromorphic computing architectures that can achieve brain-scale efficiency for complex machine learning through a multi-disciplinary approach spanning device physics,...

This Project Grant award, provided by the National Science Foundation (NSF) under the Integrative Activities (IA) program (CFDA 47.083), funds the development of a novel hybrid CMOS+X-based in-memory analog computing framework at the University of Oklahoma. The $189,000 award, effective May 1, 2025 through April 30, 2028, aims to emulate the energy efficiency of the human brain through neuromorphic computing utilizing 3D NAND flash memory chips and molecular memristors as artificial synapses...