Project Grant 2513734
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides funding of $150,843 to the University of Wisconsin System for a 2-year project titled "DEVELOPMENT OF AN EXPERIMENTAL BASIS FOR LARGE LANGUAGE MODEL (LLM) HYPOTHESIS GENERATION TOWARD MATERIALS DESIGN". The project aims to establish a framework for ingesting and leveraging multimodal data from experiments, such as graphs, tables, and microscopy images,...
- This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences program (CFDA 47.049) supports a project at the University of Utah focused on using advanced natural language processing and large language models to automatically extract materials data from scientific literature. The $200,000 award, made on an EAGER proposal, aims to tackle the challenge of materials data being locked in unstructured PDF formats that are difficult to utilize in modern...
- This Project Grant award of $300,000 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program supports a study at Georgetown University to develop an evaluation methodology for measuring the impacts of implementing large language model (LLM)-based tools to assist human experts working in federal, state, and local government programs. The project will compare the performance of LLM-only, human-only, and human-LLM hybrid responses across key metrics...
- This $174,995 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to understand and optimize the role of human intelligence in data integration and discovery pipelines, especially in the context of emerging large language models (LLMs) like ChatGPT. The project will investigate fundamental questions about human involvement in these data processes, uncover relevant human biases, and...
- This Project Grant award of $600,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a performance period from October 1, 2025 to September 30, 2028, will support the establishment of a new data curation infrastructure. The project aims to integrate large language models (LLMs) and vector indexing into the scientific data life cycle to improve metadata, enhance discoverability, and optimize data storage. This will address...
- This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to revolutionize materials discovery by integrating physical principles into deep learning models. The $500,000 award, granted on June 15, 2025, with a completion date of November 30, 2026, will enable the Regents of the University of Minnesota to develop innovative machine learning techniques that can rapidly and...
- This $185,163 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) supports the development of scalable Gaussian process methods for spatial statistics and machine learning. The project aims to create a universal toolbox for highly accurate and computationally efficient Gaussian process modeling to enable improved data analysis, prediction, and uncertainty quantification across diverse applications like carbon monitoring,...
- This Project Grant award from the National Science Foundation (NSF) under the Integrative Activities program (CFDA 47.083) will support the development of novel deep generative models and algorithms for analyzing and visualizing scientific texts. The $224,036 award to New Mexico State University (NMSU) will fund a fellowship for an assistant professor and graduate student training. The project aims to create algorithms that model the intent, topics, and embeddings within scientific documents, as...
- This federal Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $250,000 to Cornell University to develop new statistical models and methods for analyzing data from large language models (LLMs). The project "SOFTMAX MIXTURE ENSEMBLES FOR LEVERAGING LLM OUTPUT" aims to create computationally efficient techniques for summarizing and interpreting the complex, high-dimensional outputs of current LLMs, which...
- The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Wisconsin System for the project "Collaborative Research: III Small: Towards Large Open-World Foundation Models: Construction, Adaptation, and Deployment." The project, running from August 1, 2025 to July 31, 2028, aims to develop new algorithms, theorems, and systems to improve the reliability of advanced artificial...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $269,717 to the University of Wisconsin-Madison to develop an infrastructure for accurately extracting data and related knowledge from scientific papers using large language models (LLMs). The project aims to refine the use of LLMs, such as ChatGPT, to automate the complex task of reading thousands of scientific papers and extracting key materials data, including from text, tables, and plots. The resulting web interface will allow researchers, engineers, and entrepreneurs to quickly access and utilize this curated materials data, helping to accelerate technological developments across industries that rely on advanced materials. The project runs from September 1, 2025 to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $269.7k | 8/7/25 |