This Project Grant award, valued at $189,000.00 and funded by the National Science Foundation's Integrative Activities program (CFDA 47.083), supports the development of a novel hybrid CMOS+X-based in-memory analog computing framework. The key products and services to be delivered under this grant include: The framework will utilize industry-scale 3D NAND flash memory chips to create massive arrays of artificial synapses, mimicking the human brain's 100 trillion synapses. These artificial...
This Project Grant award of $210,000.00 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program supports an interdisciplinary research effort at Arizona State University (ASU) to develop an efficient, situation-aware artificial intelligence (AI) processing system leveraging emerging spin-orbit torque magnetic random access memory (SOT-MRAM) technology. The key products and services to be delivered under this award include: 1) exploring novel...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,200,000 to Purdue University to develop scalable and ultra-low-power neural accelerators based on 2D ferroelectric semiconductors. The research aims to address hardware needs for future artificial intelligence (AI) platforms by utilizing the unique properties of ferroelectric semiconductors to design energy-efficient circuits and...
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,...
The National Science Foundation (NSF) awarded a $500,000 Project Grant to Northwestern University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of application-specific integrated circuit (ASIC) prototypes that leverage complementary metal-oxide semiconductor (CMOS) circuits integrated with voltage-controlled magnetic memory devices to enable probabilistic computing. The key products to be delivered through this 3-year project...
The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Engineering program (CFDA 47.041) to the University of Arizona for the period of June 1, 2024 to May 31, 2027. The project, titled "COLLABORATIVE RESEARCH: SPINTRONICS ENABLED STOCHASTIC SPIKING NEURAL NETWORKS WITH TEMPORAL INFORMATION ENCODING," aims to develop novel neuromorphic computing architectures that leverage the temporal information encoding capabilities of stochastic magnetic devices. The...
The National Science Foundation Division of Information and Intelligent Systems awarded a $143,624 Project Grant to the University of Georgia Research Foundation, Inc. under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will support a collaborative research project between multidisciplinary investigators to leverage advances in neuroscience data and develop brain-inspired artificial intelligence. Specifically, the researchers will analyze...
The National Science Foundation (NSF) awarded a $174,229 Project Grant under the Computer and Information Science and Engineering (CISE) program to Michigan Technological University. The grant, awarded on October 1, 2023, with a completion date of September 30, 2025, is focused on developing a self-learning neuromorphic robot system that can operate efficiently in resource-constrained environments. The key objectives of this research project are to: 1) create a neuromorphic robot that utilizes...
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 $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...