Project Grant 2551510
- The National Science Foundation Division of Computing and Communication Foundations awarded Georgia TECH Research Corp $149,746 on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to investigate the neural correlates of complexity in data visualizations. The research bridges human-computer interaction and neuroscience to establish a theory-driven, predictive framework for understanding how specific visualization design elements foster or hinder...
- The National Science Foundation awarded Georgia TECH Research Corp, doing business as the Office of Sponsored Programs, $301,630 under the CAREER program in Computer and Information Science and Engineering (CFDA 47.070) on July 1, 2026. The project advances research on trust calibration in data visualizations across science, education, healthcare, and other domains. The team will develop methods to measure user trust in data visualizations using social science theories and methodologies, conduct...
- The National Science Foundation Division of Computing and Communication Foundations awarded Georgia TECH Research Corp $354,774 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070). The award funds development of computational tools that connect natural animal behavior to brain activity, with the goal of understanding how the brain supports flexible decision-making in complex environments. The work will employ inverse reinforcement learning...
- Federal Grant Award Summary Georgia TECH Research Corp received a $421,652 Project Grant from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), awarded April 15, 2025, with completion targeted for October 31, 2027. This collaborative research initiative examines confirmation bias in visual data analysis and develops mitigation strategies to improve data-driven decision-making. The project delivers four primary...
- The National Science Foundation Division of Information and Intelligent Systems awarded Georgia TECH Research Corp $386,963 on July 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct research treating artificial intelligence data center infrastructure as a cyber-physical system that responds to hardware thermal and power constraints during distributed training. The project addresses a fundamental gap in AI training systems: current software...
- The National Science Foundation Division of Computing and Communication Foundations awarded The University of Chicago $402,391 on June 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for research on responsible data visualization design. The project, titled "Seeing What Matters: Reframing Visualization as Data Disclosure," develops theory and software tools to help visualization authors balance ethical communication goals—including effective...
- Grant Award Summary Georgia TECH Research Corp received a $200,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070: Computer and Information Science and Engineering) awarded July 15, 2025, with completion targeted for June 30, 2028. This collaborative research initiative addresses the integration of human perception into database systems and sampling algorithms for visual analytics applications. The project delivers research and...
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...
- The National Science Foundation Division of Computing and Communication Foundations awarded Georgia State University Research Foundation Inc. $406,481 on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop medical artificial intelligence systems that are computationally efficient, robust to incomplete patient data, and interpretable to clinicians. The project will create vision-language models that learn to separate visual information...
- The National Science Foundation Division of Computing and Communication Foundations awarded Georgia TECH Research Corp $749,999 on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop scalable bilevel optimization algorithms and computational tools for machine learning systems. The project addresses computational bottlenecks in bilevel optimization—a mathematical structure where an overarching objective depends on a nested subordinate...
The National Science Foundation Division of Computing and Communication Foundations awarded Georgia TECH Research Corp $400,173 on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to study responsible AI guidance in visual data analysis tools. The recipient will develop a modular software testbed with AI guidance components for chart creation and visual analysis of tabular data, then design computational metrics to measure real-time reliance on AI suggestions and detect both under-reliance and over-reliance. The team will conduct controlled user studies to determine which visual analytics tasks benefit most and least from AI guidance, establish baselines for appropriate utilization, and design user interface components that detect suboptimal guidance usage and prompt more effective engagement. The testbed and associated code will be released as open-source resources. The project runs from October 1, 2026, through September 30, 2029, and is performed at Georgia Tech in Atlanta, Georgia. The findings are intended to support responsible design of AI-powered visual data tools across business, healthcare, and national security applications, maintaining meaningful human control as AI capabilities advance.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $400.2k | 7/26/26 |