This Project Grant award from the National Science Foundation's STEM Education program (CFDA 47.076) will support the development of a novel plugin for the Common Online Data Analysis Platform (CODAP) to visualize data privacy concepts for teaching, as well as create associated learning modules for integrating into privacy curricula. The $500,000 project will also empirically investigate the use of storytelling visualization techniques to improve pedagogical practices for teaching data...
The National Science Foundation (NSF) awarded a $387,044 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University to improve the fundamental limits of privacy-enhancing technologies (PETs). The research aims to develop new PET methods that optimize the balance between preserving individual privacy and enabling comprehensive data analysis for societal benefit in domains such as healthcare, education, and resource allocation. Key...
The National Science Foundation (NSF) awarded a $599,518 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Maryland, College Park. This five-year grant, which began on September 1, 2023, will support research into "Manipulable Semantic Components in Data Visualization Design." The key focus of the project is to develop new interaction paradigms for data visualization design, enabling flexible manipulation of graphical...
This $343,324 National Science Foundation project grant supports research at Northeastern University to develop empirically validated perceptual tasks for data visualization. The goal is to refine and evaluate a model of the lower-level perceptual processes underlying higher-level data analysis and visualization tasks. Researchers will conduct qualitative studies to document how people decompose tasks and then empirically evaluate proposed perceptual subtasks like filtering images, judging...
The National Science Foundation (NSF) awarded a $179,055 Project Grant to the University of Virginia under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports collaborative research to develop privacy-preserving algorithms for fundamental problems in graph mining and network science. The project aims to create scalable, accurate graph differential privacy algorithms for applications like healthcare, social networks, finance, and computational...
The National Science Foundation awarded a $249,703 Project Grant to the Trustees of Boston University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will fund research from October 1, 2022 to September 30, 2025 to develop methods for integrating legal and technical approaches to privacy in the design of sociotechnical software systems. Specifically, the project aims to establish technical interpretations of legal privacy concepts that...
This Project Grant award, valued at $199,997.00, was granted by the National Science Foundation (NSF) under its Mathematical and Physical Sciences (CFDA 47.049) federal grant program. The award, titled "Advancing Privacy and Security in Complex Networks by Statistical Algorithms: Safeguarding, Monitoring, and Remediation," focuses on improving data privacy and security within complex networks through a comprehensive strategy. The key products and services to be delivered under this...
The National Science Foundation Division of Computer and Network Systems awarded a $199,076 Project Grant to the FPF Education And Innovation Foundation for collaborative research titled "A Large-Scale, Longitudinal Resource to Advance Technical and Legal Understanding of Textual Privacy Information." The three-year award runs from July 1, 2021 to June 30, 2024 under the Computer and Information Science and Engineering program (CFDA #47.070). The grant will support the development of a...
The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Illinois for a 4-year collaborative research project on privacy-preserving machine learning on graph-structured data. The project aims to develop innovative, efficient algorithms for training and updating large-scale graph neural network models while preserving the privacy of sensitive graph data across applications in areas...
This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $1.2 million to the University of North Carolina at Chapel Hill to develop counterfactual-centered methods for data visualization from October 1, 2022 to September 30, 2026. The university will design and implement new computational techniques and open-source software to enhance traditional data visualization tools. By incorporating comparisons to counterfactual data...