Project Grant 2544071
- Federal Grant Award Summary Washington State University received a $317,381 CAREER (Faculty Early Career Development) Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), awarded on June 15, 2025, with completion by May 31, 2030. The award supports a comprehensive five-year research initiative to develop innovative methods for integrating conformal prediction...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a CAREER grant of $417,565 to The Washington University (Office of Sponsored Research Services) beginning October 1, 2026, and extending through September 30, 2031. Under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), this project will develop an adaptive knowledge synthesis framework that enables large language models (LLMs) to...
- Federal Project Grant Award Summary The University of Washington received a $370,692 CAREER award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CFDA 47.070) program, effective June 15, 2025, through May 31, 2030. This project addresses the critical challenge of Large Language Model (LLM)-generated content in online information ecosystems by developing an epistemological framework to...
- Federal Grant Award Summary Washington State University received a $474,787 CAREER (Faculty Early Career Development) Project Grant from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering program (CFDA 47.070), awarded August 15, 2025, with completion targeted for July 31, 2030. The project delivers research and development services focused on identifying and mitigating covert timing channels in real-time...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a CAREER grant totaling $315,154 to the Regents of the University of California at Riverside on July 1, 2026, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The project, "Redefining Testing Foundations for Heterogeneity-Aware AI Compilation," will operate through June 30, 2031, and develops a cross-layer testing framework to...
- Federal Grant Award Summary Purdue University received a $391,123 CAREER award from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), effective September 1, 2026 through August 31, 2031. The project develops novel formal methods techniques and a trustworthy framework for software developers to rigorously explore, examine, and understand the behavior of potentially flawed...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a $600,000 CAREER grant under the Engineering program (CFDA 47.041) to the University of California, Santa Barbara, effective April 15, 2026, through March 31, 2031. This project grant supports foundational research and algorithm development in Large Language Model (LLM) watermarking techniques designed to embed hidden, decodable signals into AI-generated text. The...
- Federal Grant Award Summary Wayne State University received a $500,000 project grant from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), effective October 1, 2025 through September 30, 2030. This CAREER award funds fundamental research into trustworthy sequential decision-making systems, specifically addressing the integration of privacy, robustness, and fairness within reinforcement learning (RL)...
- Federal Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded The Leland Stanford Junior University a CAREER grant totaling $414,320 on June 1, 2026, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to develop error-resilient algorithmic solutions for emerging hardware technologies. The project will deliver software tools and mathematical foundations enabling artificial intelligence (AI) algorithms...
- Federal Grant Award Summary This NSF CAREER award, totaling $560,000 and administered through the Engineering program (CFDA 47.041), funds a five-year project (April 1, 2026 – March 31, 2031) at Rochester Institute of Technology to develop adaptive machine learning systems capable of continuous learning without catastrophic forgetting. The primary deliverables include fundamental algorithms and theoretical frameworks for continual learning that leverage Bayesian uncertainty quantification,...
Washington State University received a $326,994 CAREER (Faculty Early Career Development) Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), effective June 1, 2026 through May 31, 2031. The award supports research and development of novel methodologies for improving the reliability and adaptability of foundation models—large artificial intelligence systems used across science and technology sectors. The primary deliverables include a new information flow representation framework that reshapes how large AI models transmit information to enable more reliable assessment of model outputs, and a unified computational framework for systematically integrating diverse data sources with established scientific knowledge. These technical advances are designed to address critical gaps in identifying when foundation model outputs are unreliable, particularly in safety-critical applications such as health monitoring and smart home systems. The research approach treats internal model stages as information flow snapshots, enabling structured uncertainty tracking in lower-dimensional spaces to provide scalable reliability estimates applicable to large-scale models. Key products include methods supporting adaptation to new data modalities from emerging sensors and mechanisms for incorporating scientific laws and domain knowledge into model operations. Beyond technical research outcomes, the grant supports workforce development activities focused on training practitioners in leveraging foundation model technologies responsibly and implementing trustworthy decision-support systems. The five-year project timeline reflects the CAREER program's emphasis on integrating research innovation with educational components for early-career faculty development.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $327.0k | 5/1/26 |