Project Grant 2440153
- The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Integrative Activities program (CFDA 47.083) to the University of South Alabama. The two-year award, effective January 1, 2025, supports research on memristor-based computing-in-memory (CIM) for neuromorphic systems. The project aims to investigate the design, optimization, and fabrication of memristor-based CIM technology for energy-efficient artificial intelligence (AI) computation, with a focus on emerging AI...
- The University of Oklahoma was awarded a $189,000 Project Grant by the National Science Foundation's Integrative Activities program (CFDA 47.083) on May 1, 2025. The project aims to develop a novel hybrid CMOS+X-based in-memory analog computing framework that utilizes industry-scale 3D NAND flash memory chips and academic laboratory-scale molecular memristors. This framework seeks to emulate the efficiency of the human brain by creating trillions of artificial synapses and nano-scale nonlinear...
- This $211,129 project grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at Northeastern University to develop a design framework for efficient information processing using non-binary representations and in-memory computation. The project aims to advance analog/mixed-signal design automation, create intelligent and flexible in-memory computing architectures, and explore energy-efficient...
- This Project Grant award for $200,000 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research by Southern Illinois University Carbondale (SIU) to develop hardware-constraint-aware design and optimization techniques for memristor-crossbar-array (MCA) based neural network accelerators. The research aims to bridge the gap between software design tools and the physical limitations of MCA hardware, enabling more efficient and cost-effective development of...
- This $250,000 Project Grant, awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program, supports a collaborative research effort focused on developing formal methods to synthesize and verify in-memory computing systems for neural networks. The project aims to: Verify the reliability of analog and digital in-memory computing (IMC) circuits used to accelerate neural networks, and Leverage machine learning and formal methods to synthesize...
- 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 $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 award under the Engineering program (CFDA 47.041) provides $275,000 to develop a novel brain-inspired processor-in-memory system powered by environmentally-sustainable carbohydrate-based memristors. The key objectives are to create an energy-efficient, renewable, and ecologically-friendly computing solution to address sustainability challenges in artificial intelligence (AI) systems and computing devices. The project will leverage innovative...
- 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...
- The University of Michigan was awarded a $390,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to develop highly efficient bio-inspired edge computing systems. The project aims to leverage internal ionic, electronic, and thermal dynamic processes in emerging devices and networks to directly process spatiotemporal data with high performance, energy efficiency, and reliability. The research will focus on...
This federal Project Grant award, valued at $198,270.00 and provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports conceptualization, planning, and collaboration activities to develop a comprehensive research roadmap for a novel hybrid CMOS+X in-memory analog computing framework. The planning grant will catalyze multidisciplinary collaboration among experts in materials science, circuit design, neuroscience, and artificial intelligence (AI) to co-design hardware accelerators and bio-inspired learning algorithms. Key activities include organizing "un-workshops", engaging with industry leaders, conducting feasibility studies on integrating emerging devices like memristors with scalable CMOS technology, and exploring brain-inspired principles such as predictive coding. These efforts aim to identify critical research questions, assess infrastructure and fabrication compatibility, and inform a future competitive CISE LARGE proposal to launch a transformative initiative focused on developing a new class of computing hardware that mimics the brain's efficiency, paving the way for advances in AI performance, semiconductor technology, and workforce development.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $198.3k | 8/5/25 |