Project Grant FA86552517466

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 $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) project grant, awarded under the Engineering (CFDA 47.041) program, supports the development of new optical devices called "intersubband neurons" that could enable ultrafast optical neural networks. The $352,180 award to the University of Texas at Austin, running from October 1, 2023 to March 31, 2026, aims to create these novel photonic devices that can perform computations at the speed of light, potentially outpacing electronic neural...

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 $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 $424,750 Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) supports the development of an ultrashort-pulse optical neural network system for brain-scale computing. The research aims to leverage the speed, bandwidth, and low-loss properties of light to enable real-time processing of billion-scale neural network models using minimal spatial elements. This approach seeks to overcome the limitations of current optical computing architectures. The...

This Project Grant award of $238,794 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research to develop efficient and robust artificial intelligence (AI) hardware systems inspired by the human brain. The project aims to leverage novel magneto-electronic (spintronic) technologies to create computational components that emulate neural stochastic functionality. These components will be integrated into in-memory...

This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $467,930 to Northeastern University to design and implement a novel class of metasurface-based optical neural networks, termed "meta-ONNs". The goal is to develop multiplexed meta-ONNs that can operate at optical frequencies and perform diverse functions like all-optical image recognition and pattern generation. The project consists of three main research thrusts: (1)...

This three-year, $279,334 National Science Foundation project grant funds research at the New Jersey Institute of Technology to develop integrated sensing and normally-off computing architectures for Internet of Things devices. The research focuses on designing processing-in-sensor units and processing-near-sensor units that co-integrate sensing and processing capabilities. These hybrid platforms will feature granularly configurable arithmetic operations to balance accuracy, speed and power...

This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) project grant award provides $650,000 to The Trustees of Columbia University in the City of New York to develop energy-efficient optical brain-inspired (neuromorphic) computing devices. The project aims to establish a 3D nanofabrication platform that combines DNA-programmable assembly and conventional lithographic methods to create novel optical metamaterials and integrate them into neuromorphic...