Project Grant 2453035
- The University of Florida was awarded a $1,188,351 project grant from the National Science Foundation under the Computer and Information Science and Engineering grant program (CFDA 47.070) to develop a privacy-preserving cyber infrastructure for collaborative smart farming. The three-year award beginning June 1, 2023 will support the creation of a federated analytics framework to enable data and model sharing between agricultural farms while preserving individual data privacy. A novel...
- The National Science Foundation awarded a $305,228 Project Grant to Stanford University from the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the period of September 1, 2022 through August 31, 2025. The grant will support research investigating how emerging digital technologies are transforming occupations and organizations in the dairy farming industry. Specifically, the research will explore evolving relationships between people, sensors, data,...
- This three-year Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $349,632 to the University of California, Santa Barbara for collaborative research exploring how emerging digital technologies are transforming occupations and organizations in the dairy farming industry. Specifically, the research will investigate evolving relationships between people,...
- This Project Grant award of $195,013 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will establish the AI4AG living lab at Cornell University. AI4AG will serve as an accessible testbed to accelerate the development and deployment of artificial intelligence (AI) technologies for agriculture. The project will create a shared space equipped with tools, data, and expertise to support AI research and testing in real-world agricultural...
- The National Science Foundation (NSF) awarded a $379,224 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Pennsylvania State University. The project, titled "CAREER: PRIVACY AUDITING FRAMEWORKS AND DEFENSES FOR MACHINE LEARNING MODELS TRAINED ON TABULAR DATA," aims to develop methods for assessing and mitigating privacy risks in machine learning (ML) models trained on sensitive tabular data, such as patient records or financial...
- This $173,754 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop an innovative privacy-preserving federated learning (FL) framework suitable for heterogeneous edge devices. The key objectives are to: 1) enable tailored device-specific models to mitigate biases and enhance performance across diverse computational capabilities and data distributions, 2) utilize differential privacy...
- This National Science Foundation project grant of $599,999 will fund research at Duke University from October 2022 through September 2026 towards developing secure methods for federated learning. Federated learning is an emerging machine learning technique that allows analysis of private data without centralized collection, but current methods lack security protections. Under the Computer and Information Science and Engineering program (CFDA 47.070), the researchers will explore new security...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop a database architecture that integrates privacy regulations and compliance processes, enhances federated machine learning with decentralized data management functions, and automates privacy-model configuration in artificial intelligence workflows. The $249,998 award to Arizona State University will be used to address the...
- This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program, CFDA #47.070, provides $265,054 to Weill Medical College of Cornell University to develop a consolidated framework for computational privacy and machine learning from October 1, 2022 to September 30, 2026. The framework aims to comprehensively consider optimal tradeoffs between privacy protections and critical machine learning properties like predictive utility, fairness, and...
- The National Science Foundation awarded a $304,786 project grant to the Donald Danforth Plant Science Center under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a cyber-physical system for securely sharing agricultural data and lessons learned via edge computing. The three-year award beginning October 1, 2022 will support intersecting expertise in plant science, secure networked systems, software engineering, and geospatial science to mitigate challenges...
This Project Grant award, titled "PDASP TRACK 3: PRIVACY-PRESERVING DAIRY-DIGITALIZATION WITH FEDERATED LEARNING", is funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The $376,178 award to Cornell University will develop a secure digital platform that allows dairy farmers to collaboratively benefit from advanced artificial intelligence without sharing their private farm data. The platform will include user-friendly computer assistants that can understand everyday language and provide personalized, data-driven recommendations to help farmers improve their operations. This work aims to promote scientific progress in agriculture, advance national prosperity and welfare through more efficient and sustainable food production, strengthen agricultural data security, and support the competitiveness of American agriculture in global markets.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $376.2k | 8/19/25 |