Project Grant 2520486
- This $250,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research by the University of Washington to explore the use of machine learning and artificial intelligence algorithms to augment limited datasets and improve statistical inference. The project will take a three-pronged approach: 1) establishing new semi-parametric efficiency results for semi-supervised learning, 2) developing new and improved...
- This $175,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research to develop new statistical and computational methods to enhance the reliability of data analysis in modern, large-scale datasets, particularly in the era of AI. The key areas of focus include: (1) analyzing the robustness of manifold and deep learning algorithms for high-dimensional, noisy, and nonlinear data; (2) developing statistical theory...
- This Project Grant award of $165,000.00 from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research at Clemson University to develop a comprehensive framework for the principled use of artificial intelligence (AI) technologies in data-intensive education research. The project aims to benefit society by enabling more trustworthy education research, fostering public confidence in AI applications, and ensuring technological advances serve all...
- This $140,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will develop a next-generation statistical framework to improve the reliability and reproducibility of data science (DS) and artificial intelligence (AI) methods. The project, titled "Collaborative Research: Performance Guaranteed Statistical Learning with Multiple Classes of Models (Guided by PCS)," aims to advance a framework called...
- The National Science Foundation (NSF) awarded a $500,000 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to the University of Washington. The grant, entitled "HCC: SMALL: D3 AND ME: MAKING VISUALIZATION TOOLKITS EASIER TO LEARN THROUGH PERSONALIZED KNOWLEDGE GRAPHS", will fund the development of an online platform to help university students more effectively learn complex data visualization tools like D3. The objective is to model...
- This Project Grant award of $200,000 from the National Science Foundation's STEM Education (47.076) program aims to promote AI readiness and democratize AI technologies for a broad spectrum of advanced cyberinfrastructure users and researchers. The key products and services provided under this 4-year award, which began on September 1, 2023, include: Developing a comprehensive suite of experiential learning modules, including flexible micro-modules and immersive extended reality experiences, to...
- This $399,162 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop interpretable, stable, and mass-conserving artificial intelligence (AI) models to improve the computational speed and efficiency of geoscientific models, such as those used for air pollution and climate research. The project will create simpler "surrogate" machine learning models for key components like atmospheric chemistry and wildfire plume rise, allowing for...
- This $175,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development of a unified generative prediction and inference framework using diffusion processes, normalizing flows, and transfer learning to model joint distributions of tabular and unstructured data. The key products and services delivered under this award include: Algorithms for domain adaptation, reliability metrics for trustworthy AI,...
- This $225,431 federal Project Grant award from the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a collaborative research project at The Washington University that uses machine learning to create a comprehensive database of State of the State addresses from 1800 to 2016. The project involves collecting, cleaning, and processing the full set of speeches from U.S. state governors over time, leveraging novel techniques to...
- This $599,411 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a "Trustworthy Toolbox for Double-Correct Predictive Modeling in Sciences." The project aims to create advanced artificial intelligence (AI) and machine learning (ML) models that can make accurate predictions while also providing transparent, scientifically-grounded rationales for their outputs. This...
This Project Grant award, valued at $325,000.00, was provided by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Washington. The project develops powerful new tools for understanding complex data, leveraging cutting-edge artificial intelligence (AI) techniques to help data analysts across diverse fields make informed, automated decisions. The research introduces novel approaches to analyze messy, heterogeneous, and large datasets - methods that are fast, flexible, explainable, and AI-powered. These tools will help scientists and decision-makers identify patterns, quantify uncertainty, and make better data-driven decisions. In parallel, the project aims to advance public education in data science and mathematics by creating learning opportunities for high school and college students and bringing cutting-edge ideas into classrooms and community events. The award period runs from September 15, 2025, to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $325.0k | 8/26/25 |