Project Grant 2531897
- This Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of machine learning methods for estimating the risk of adverse weather and climate events, such as rapid changes in solar power generation and flooding. The University of Hawaii at Manoa, as the prime contractor, will apply advances in generative artificial intelligence...
- This National Science Foundation (NSF) Project Grant, under the Office of International Science and Engineering program (CFDA 47.079), will provide $100,000 in funding to Arizona State University (ASU) to harness artificial intelligence (AI) methods to automate the design and characterization of nucleic acid nanodevices. The overarching goal is to develop novel generative AI techniques to streamline the design process for these complex bionanotechnology structures, which have promising...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $274,636 to Rensselaer Polytechnic Institute (RPI) to conduct research on developing energy-efficient and scalable artificial intelligence (AI) systems. The key objectives are to: 1) leverage dynamic connectivity in AI models to reduce redundancy and energy consumption, 2) explore heterogeneous architectures integrating approximate,...
- This $471,529 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to expand the understanding of large language models (LLMs), a type of artificial intelligence (AI). The project at the Trustees of Boston University aims to move beyond identifying simple, binary concepts within LLMs and instead develop methods to discover and characterize more sophisticated, multi-dimensional...
- 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 federal Project Grant award of $100,000.00, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports research on advanced probabilistic models and their application to cutting-edge machine learning techniques. The research aims to bring mathematical rigor and develop new methods related to complex systems in areas such as image processing, reinforcement learning, and generative AI. Key focus areas include: 1) extracting...
- This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support research at Brown University to develop novel machine learning (ML) and artificial intelligence (AI) methods for modeling and interpreting cosmological 21 cm emission from neutral hydrogen in the early universe. The $291,477 award, effective from October 1, 2025 to September 30, 2028, aims to provide insights into the...
- This federal Project Grant award of $500,000.00, granted by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070), aims to develop an innovative deep learning framework that combines physics-informed principles with scientific domain-adapted generative diffusion models. This research will address key challenges in scientific inverse design and accelerate scientific discovery, particularly in the field of nanophotonics. The...
- This $199,040 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop new classes of computational algorithms that combine the benefits of direct computer simulations and the speed of machine learning predictions. The project, titled "XTRIPODS: HYBRID SCIENCE-MACHINE LEARNING SOLVERS FOR NANOPHOTONICS AND METAMATERIALS," will embed scientific knowledge into the machine learning...
- This $375,213 Project Grant awarded by the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) will fund a facilitated workshop to identify translational research opportunities for improving the energy efficiency and scalability of leading artificial intelligence (AI) and machine learning (ML) models. The workshop will bring together AI/ML researchers and model builders to generate at least five collaborative project concepts for incorporating research...
This Project Grant award from the National Science Foundation (NSF) under the Integrative Activities program (CFDA 47.083) provides $299,989 to the University of Hawaii at Manoa to develop artificial intelligence (AI) tools to interpret data from the Linac Coherent Light Source at SLAC National Accelerator Laboratory. The goal is to create a scalable framework that integrates vision-language models, physical constraints, and experimental data to extract dynamic signatures from high-throughput X-ray scattering patterns. This work will enhance the Principal Investigator's expertise and support AI-driven computational imaging to advance applications such as improving solar panel and battery efficiency, biomedical imaging, radiation therapies, and the design of new materials and precision drugs. The award term is from January 1, 2026 to December 31, 2027.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 9/15/25 |