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...
The University of California, Santa Barbara received a $500,000 Project Grant award from the National Science Foundation on August 15, 2021 to develop an integrated unipolar-0.5T0.5R RRAM crossbar array for neuromorphic computing. The project aims to advance research supported by the Computer and Information Science and Engineering program (CFDA #47.070) through July 31, 2024. Specifically, the university will utilize the funding to create a novel resistive random-access memory (RRAM)...
This Project Grant award from the National Science Foundation (NSF) under its Engineering program (CFDA 47.041) provides $400,000 in funding to Yale University to develop a new hardware system for accelerating the computational modeling of continuous neuronal systems. The project aims to address the significant computational demands required for sophisticated multi-scale brain models by creating a convergent simulator architecture that leverages neuromorphic hardware principles. The resulting...
The National Science Foundation awarded University of California Irvine a $499,793 Project Grant under the federal Computer and Information Science and Engineering grant program (CFDA 47.070). The grant will support the development of brain-inspired machine learning algorithms to provide real-time feedback to sensors and intelligently control data generation rates. This is expected to reduce sensor data outputs by up to four orders of magnitude for applications in infrastructure, mobile devices,...
The National Science Foundation (NSF) has awarded a $330,000 Project Grant under the Engineering program (CFDA 47.041) to Yale University. The "NeroFlex" project aims to develop an advanced implantable neural interface platform that integrates optimized resistive RAM memory, programmable analog front-end circuits, and specialized processors for efficient brain data acquisition and computational processing. The research plan encompasses device fabrication, mixed-signal circuit design,...
The National Science Foundation awarded a $525,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) to support research investigating energy-efficient persistent learning-in-memory with quantum tunneling dynamic synapses from October 1, 2022 to September 30, 2025. The award will fund the development of novel learning hardware and software tools to significantly improve the energy efficiency of artificial...
The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the University of California, San Diego (UCSD) under the Computer and Information Science and Engineering (CFDA 47.070) program. The 3-year grant, effective July 1, 2023, supports research to develop dynamic neural network architectures that can efficiently enable multimodal perception, including vision, audio, and language processing. The research aims to address...
The National Science Foundation (NSF) Directorate for Engineering (CFDA #47.041) awarded a $360,000 Project Grant to the University of California, Irvine (UC Irvine) to develop advanced "neurally-inspired" technology for seamlessly integrating communication and machine learning. The key products and services to be delivered under this 3-year grant are: (1) Designing rigorous communication schemes that leverage redundant and holographic neural representations to achieve...
The University of California, Santa Barbara (UCSB) was awarded a $599,997 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program. The funding will support the development of innovative machine learning technology to address productivity and quality challenges in integrated circuit (IC) design and manufacturing. The project aims to create a semi-supervised learning framework to enable data-efficient circuit optimization,...
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...
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 "one-shot" learning, and variation-tolerant in-memory computing hardware circuits. UCSB is collaborating with Technische Universitaet Graz, Yale University, and New York University's School of Medicine to advance the project's algorithmic and hardware development through sub-awards. Specifically, the sub-awardees are contributing expertise in spiking neural network learning algorithms, neuromorphic circuit design, and reinforcement learning modeling. The proposed research seeks to address challenges in scaling up artificial intelligence systems while leveraging insights from biological neural networks.