Project Grant 2608771
- Federal Project Grant Award Summary Case Western Reserve University's Office of Research Administration has received a $420,000 CAREER award from the National Science Foundation (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CFDA 47.070) program, effective October 1, 2026 through September 30, 2031. The project addresses a critical limitation in foundation models—large artificial intelligence systems trained on vast...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a $600,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) for the period July 1, 2026 through June 30, 2029. The award supports research into selective prediction techniques for large visual-language models designed to improve the trustworthiness and safety of artificial intelligence...
- Federal Project Grant Award Summary Michigan State University received a $600,000 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 August 1, 2025, with completion anticipated July 31, 2028. The project, titled "III: SMALL: Enhancing Adversarial Robustness of Geospatio-Temporal Models," will develop robust artificial intelligence (AI)-based...
- Federal Project Grant Award Summary Carnegie Mellon University's Office of Sponsored Programs received a $100,000 Project Grant award 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), effective September 1, 2025, through August 31, 2028. This collaborative research initiative, titled "Mathematical Frontiers of Generative AI," aims to develop rigorous...
- Federal Project Grant Award Summary Carnegie Mellon University received a $508,043 project grant awarded August 1, 2025, under the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) to develop robust machine learning (ML) systems capable of withstanding adversarial attacks and data distribution shifts. The five-year award, extending through July 31, 2030, funds research establishing a "robustness via analysis" framework that bridges...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a $180,000 Project Grant to Trustees of Tufts College beginning October 1, 2025, and concluding September 30, 2027, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This collaborative research initiative addresses intellectual property protection challenges arising from the use of generative artificial intelligence (AI) in...
- Federal Project Grant Award Summary New York University received a $420,000 Project Grant award from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025 through September 30, 2028. This collaborative research initiative evaluates the security landscape of machine learning (ML) and artificial intelligence (AI) enabled electronic design automation (EDA) tools...
- Federal Project Grant Award Summary AIGIS: Securing the Deep Learning Model Supply Chain The National Science Foundation (NSF), Division of Computer and Network Systems, awarded Purdue University a $410,000 Project Grant (CFDA 47.070 – Computer and Information Science and Engineering) effective October 1, 2026, through September 30, 2030, to develop security methods and tools for validating the trustworthiness of pre-trained artificial intelligence (AI) models distributed through open online...
- Federal Project Grant Award Summary Wayne State University received a $266,000 collaborative research project grant awarded on October 1, 2025, 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 four-year project, scheduled for completion on September 30, 2029, advances large language model (LLM) unlearning—a technical framework enabling the targeted removal of harmful...
- Federal Project Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) awarded a CAREER grant of $354,579 to the University of Pennsylvania, effective June 1, 2026 through May 31, 2031. This project develops a comprehensive science of artificial intelligence (AI) reliability by identifying failure modes in AI systems and designing principled methods to enhance their dependability in both autonomous and human-AI collaborative...
Case Western Reserve University has received a $600,000 Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering program (CFDA 47.070), effective August 1, 2026 through July 31, 2029. The FORTEFAI (Trustworthy AI Cyberinfrastructure for Guardrailing Multimodal Foundation Models) project develops open-source, production-ready software designed to enhance the reliability and trustworthiness of artificial intelligence systems used in scientific computing and cyberinfrastructure. The core deliverable is FORTE (Finding Outliers with Representation Typicality Estimation), a model-agnostic methodology that detects distributional anomalies and out-of-distribution inputs by quantifying how closely data inputs align with the representation manifold of trusted training data. The project integrates FORTE into three coordinated software components: FORTEFAI Vision for scientific image quality assurance and out-of-distribution detection; FORTEFAI Text for large language model guardrails, hallucination detection, and prompt-injection monitoring; and FORTEFAI Log for anomaly detection in high-performance computing operations. By identifying unreliable inputs before they propagate through downstream analyses, these tools address the challenge of foundation models that often fail silently when confronted with data distributions differing from their training sets, thereby improving the robustness, reproducibility, and trustworthiness of AI-enabled scientific discovery across vision, language, and cyberinfrastructure domains.Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 6/30/26 |