This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program for $399,999 supports research to develop perception-augmented databases and sampling algorithms that optimize data visualization for efficient and robust visual analytics. The project aims to address limitations in human perception and data processing efficiency that lead analysts to work with only sampled subsets of data, which can distort insights and patterns....
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...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to democratize the use of large visual learning models by reducing the computational, data, and expertise requirements needed to create and deploy such models. The $1.2M award to Georgia Tech Research Corporation will fund research on specialized learning approaches for fast model customization with limited data, efficient inference algorithms...
This $300,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at New York University to develop efficient computer systems for augmented and virtual reality through a perception-guided approach. Specifically, the researchers will design software-hardware mechanisms to quantitatively model human visual perception and leverage those models across system stacks to achieve an order of magnitude gain in...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, aims to revolutionize data analysis by harnessing the capabilities of immersive virtual reality (VR) and augmented reality (AR) technologies. The $355,536 award to Georgia Tech Research Corporation will support the development of an end-to-end immersive data analysis workspace, with a focus on designing intuitive 3D data organization interactions,...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $421,652 to Georgia Tech Research Corp to conduct research on modeling and mitigating confirmation bias in visual data analysis. The project aims to (1) create models demonstrating how existing beliefs and analytic goals can impact data-driven decision-making, and (2) design novel analytic interfaces to help analysts make less biased decisions...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $632,000 to the University of Washington to develop advanced techniques for enabling computers to provide more effective guidance and feedback for data visualization design. The key objectives are to create "provably effective" visualization analysis methods that can be automated and integrated into visualization tools, helping...
The National Science Foundation awarded a $550,000 project grant to Arizona State University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the period of October 1, 2022 through September 30, 2025. The grant will support the development of novel techniques and open source software tools to enable the creation of privacy-preserving data visualizations. A visualization grammar will be established to specify visualization designs that consider...
This $600,000 project grant, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, will support research to develop a new Bayesian diffusion model framework for advanced visual perception and cognition systems. The University of California, San Diego (UCSD) will serve as the primary awardee, with the goal of revisiting the analysis-by-synthesis methodology by integrating generative priors into the learning and inference...
This Project Grant award of $598,555.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the development of innovative tools and techniques to enhance computer architecture analysis. The project aims to introduce advanced visualization, collaborative sensemaking, and generative AI methods to provide deeper insights into system performance, enabling the design of more efficient and sustainable computing...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $200,000 to Georgia Tech Research Corporation to develop a "perception-augmented database" and associated sampling algorithms that optimize data visualization for human perception.
The key products and services to be delivered include:
A prototype perception-augmented database with novel representations for perceptual saliency data and optimized storage strategies.
Novel sampling algorithms that use perceptual models to select data for visualization tasks, including optimizations for real-time performance.
Perception-aware compressed data representations for efficient, high-quality approximate visualizations.
New measures for evaluating the perceptual quality of data samples.
These advances are intended to enable data analysts to draw more accurate insights from visual data analysis, within a robust and efficient analytics pipeline. The project period runs from July 2025 to June 2028.