Project Grant 2435138
- The National Science Foundation (NSF) awarded a $500,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program to the Regents of the University of Michigan. The grant, titled "ACED: A UNIFIED FRAMEWORK OF PHYSICS-INFORMED AND DOMAIN-ADAPTED GENERATIVE DIFFUSION MODEL FOR EFFICIENT AND RELIABLE NANOPHOTONICS INVERSE DESIGN", aims to develop an innovative deep learning framework that combines physics-informed principles with...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) totaling $406,708 aims to develop energy-efficient AI hardware through the integration of thin-film lithium niobate with silicon photonic chip platforms. The project will design new architectures and circuit techniques to achieve high-resolution AI computation using low-precision building blocks, optimizing both efficiency and accuracy. The educational component will train students in photonic and...
- This EAGER (Early-Concept Grants for Exploratory Research) award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will develop generative artificial intelligence (AI) methods to learn from computational physics simulations and mathematical equations. The $300,000 project aims to expand the capabilities of large language models, such as OpenAI's ChatGPT and Microsoft's Copilot, to go beyond text-based learning and make predictions on complex, coupled physics problems...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to revolutionize the design and manufacturing of advanced nanocomposite materials using Artificial Intelligence (AI). The $400,000 award, with a performance period from January 1, 2026 to December 31, 2028, focuses on understanding and controlling the amorphous-crystalline interfaces within these materials to enhance their strength, durability, and reliability. The research tasks involve...
- This $618,159 National Science Foundation project grant supports research into developing energy-efficient hardware and software for machine learning and artificial intelligence systems. Funded under the Computer and Information Science and Engineering program, the award supports The Washington University in investigating frameworks using quantum-tunneling dynamic-analog memory devices and novel online learning algorithms. Specific objectives include exploring Fowler-Nordheim dynamic analog...
- 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...
- The National Science Foundation (NSF) awarded a $710,889 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Chicago. The grant, titled "COLLABORATIVE RESEARCH: FRAMEWORKS: SINAPSE: SCALABLE INFRASTRUCTURE FOR AI-COUPLED PREDICTIVE SIMULATION ENHANCEMENT," aims to develop a powerful, open-source software toolkit that combines artificial intelligence (AI) with high-performance computing (HPC) to enhance simulation...
- This $374,060 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of a novel "diffusive ferroelectric field-effect transistor (DFEFET)" device that integrates short-term and long-term memory to enable energy-efficient hardware for artificial intelligence applications. The interdisciplinary project aims to advance two key computing paradigms - spiking neural networks and physical reservoir computing - with the...
- The National Science Foundation (NSF) awarded a $252,210 Project Grant under the Integrative Activities program (CFDA 47.083) to Iowa State University of Science and Technology. The grant, with a performance period from January 15, 2025 to December 31, 2029, will fund the development of a novel system architecture using emerging devices and circuits to create intelligent computing systems based on ensembles of stochastic processing elements. This research aims to address the growing...
- 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) awarded a $549,997 Project Grant under the Engineering program (CFDA 47.041) to Northwestern University to develop a runtime physics-informed AI agent for improving the efficiency and reliability of next-generation semiconductor devices. The project aims to incorporate physics-informed machine learning techniques and energy-efficient AI accelerators to deliver intelligent chip management methods that can overcome challenges such as power supply noise, chip overheating, and device aging in advanced microelectronic devices. The award period runs from October 1, 2025 to September 30, 2028. The proposed developments are expected to bring fundamental improvements to the energy efficiency and reliability of modern microelectronic devices, which are critical to enabling emerging technologies like artificial intelligence, robotics, and 6G.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $550.0k | 7/24/25 |