Project Grant 2543591
- The Trustees of Stevens Institute of Technology received a $200,000 project grant award from the National Science Foundation under the Engineering Research Initiation (ERI) program (CFDA 47.041). The grant will fund research from July 1, 2023 through June 30, 2025 to develop a trust-supporting design framework for improving human-artificial intelligence collaboration. Specifically, the research will examine the role of affect in user trust development during interactions with conversational AI...
- Federal Grant Award Summary Award Overview The National Science Foundation's Division of Computer and Network Systems awarded a CAREER Project Grant totaling $657,779 to The Trustees of the Stevens Institute of Technology on May 1, 2026, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The five-year project, scheduled for completion by April 30, 2031, will establish scientific foundations for human-physical interaction and interaction-driven coadaptation...
- Federal Grant Award Summary Rochester Institute of Technology received a $560,000 NSF Engineering (CFDA 47.041) CAREER award effective April 1, 2026, through March 31, 2031, to develop adaptive machine learning systems for intelligent sensing technologies. The project, titled "ADAPTTRUST: Adaptable, Trustworthy and Uncertainty-Aware Learning in Intelligent Sensing Technologies," will produce fundamental research advances in continual learning algorithms, uncertainty quantification...
- Federal Grant Award Summary The National Science Foundation's Division of Computer and Network Systems awarded a $364,538 CAREER grant to The Trustees of The Stevens Institute of Technology (CFDA 47.070: Computer and Information Science and Engineering) effective July 1, 2026 through June 30, 2031. This project grant funds research toward automated vulnerability management in open-source software, delivering three primary research products: (1) enhanced patch and vulnerable code localization...
- Federal Grant Award Summary Award Details: This CAREER (Faculty Early-Career Development Program) award of $315,154 was issued on July 1, 2026, by the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The project will be conducted at the University of California, Riverside and is scheduled for completion on June 30, 2031. Products and Services: The project will deliver...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a CAREER (Faculty Early Career Development) grant of $527,459 to the University of Colorado Colorado Springs on May 1, 2026, for a five-year project period through April 30, 2031. Under the Engineering program (CFDA 47.041), this project delivers theoretical frameworks and mathematical models designed to analyze how artificial intelligence tools and heterogeneous...
- Federal Grant Award Summary The National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation awarded Georgia TECH Research Corp a CAREER (Faculty Early Career Development) grant totaling $599,972 on June 15, 2025, with a completion date of May 31, 2030. Under CFDA 47.041 (Engineering), this project grant supports the development of multifidelity scientific machine learning methods that integrate high- and low-fidelity simulation data to generate accurate predictive...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded Massachusetts Institute of Technology (MIT) a CAREER (Faculty Early Career Development) Project Grant totaling $659,678 for the period April 1, 2026 through March 31, 2031, under the Engineering program (CFDA 47.041). This award supports fundamental research on trustworthy learning-enabled autonomy, with deliverables including new mathematical theory and efficient...
- The National Science Foundation awarded a $557,806 Faculty Early Career Development (CAREER) Program grant to Lehigh University to conduct research on how the allocation of design tasks between humans and artificial intelligence (AI) agents impacts engineering design outcomes. The 5-year project seeks to develop a systematic approach for defining optimal roles for AI within hybrid human-AI design teams. It will use computational modeling and experiments with a video game platform to assess how...
- Federal Grant Award Summary The National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation awarded a $650,000 CAREER (Faculty Early Career Development) grant to the University of Pennsylvania, effective July 1, 2025 through June 30, 2030, under the Engineering program (CFDA 47.041). This project grant funds research and development of constraint-aware algorithms and control methods that enable robots to safely and effectively collaborate with humans in dynamic,...
Federal Grant Award Summary The National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation awarded Stevens Institute of Technology a CAREER (Faculty Early Career Development) Project Grant of $545,650 on September 1, 2026, for research extending through August 31, 2031. Under the Engineering program (CFDA 47.041), this award supports the development of empirical datasets, computational inference models, and trust-aware artificial intelligence (AI) adaptation strategies that estimate and respond to trust dynamics during human-AI collaboration in early-stage engineering design. The project deliverables include behavioral and psychophysiological measurement frameworks that quantify trust as a continuous, time-varying variable, coupled with formalized AI feedback mechanisms designed to calibrate designer reliance and improve human-AI interaction effectiveness. In parallel, the award funds education and outreach activities deploying AI-assisted design tools and adaptive feedback systems in undergraduate engineering courses and pre-college design bootcamps. The research aims to generate practical applications for high-stakes industrial domains including manufacturing, healthcare, and infrastructure by advancing engineering decision quality, reducing design cycle time, and supporting effective human-AI collaboration. The integrated research and educational components address National Science Foundation priorities in innovation and workforce development while producing both theoretical knowledge and deployable technologies for trust-aware AI systems in collaborative design contexts.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $545.7k | 3/13/26 |