Project Grant 2513929
- Federal Project Grant Award Summary Southern Methodist University received a $2.15 million Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering program (CFDA 47.070), awarded April 1, 2026, with a completion date of March 31, 2031. The project, titled "Framework for Advanced (Multi)Linear Infrastructure in Engineering and Science (FAMLIES)," delivers an adaptable, open-source software...
- Federal Project Grant Award Summary Carnegie Mellon University received a $389,000 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) awarded July 1, 2025, with completion targeted for June 30, 2028. This collaborative research initiative delivers correct-by-construction code generation methodologies for high-performance computational chemistry applications. The project develops novel notations and formal methods for...
- The University of Texas at Austin received a $703,154 Project Grant award from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program, effective April 1, 2026 through March 31, 2031. This collaborative research initiative delivers the Framework for Advanced (Multi)Linear Infrastructure in Engineering and Science (FAMLIES), an adaptable software framework designed to optimize matrix and tensor...
- Federal Grant Award Summary Carnegie Mellon University received a $499,934 Project Grant from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), awarded July 1, 2025, with completion targeted for December 31, 2026. The award funds development of ACED (Accelerated Graph Neural Networks for Decision-Making), a Field-Programmable Gate Array (FPGA)-accelerated Graph Neural Network (GNN) system designed to enable real-time data filtering...
- 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 Grant Award Summary Carnegie Mellon University received a $508,043 Project Grant award from the National Science Foundation's (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), with an award date of August 1, 2025, and a completion date of July 31, 2030. This CAREER award supports research to develop robust machine learning (ML) systems capable of withstanding adversarial attacks and...
- Federal Grant Award Summary Carnegie Mellon University received a $331,723 CAREER award from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective June 1, 2026 through May 31, 2031. The award supports research developing new mathematical and computational tools for solving large-scale problems involving networks, optimization, and data analysis. The project...
- Federal Grant Award Summary Carnegie Mellon University received a $250,000 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for the period September 1, 2025, through August 31, 2028. The award supports research on "Adaptive Inference by Stabilized Cross-Validation," which develops novel statistical methodologies that enable reliable uncertainty quantification and inference...
- Federal Project Grant Award Summary Carnegie Mellon University received a $675,000 project grant 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, 2025, through September 30, 2028. This collaborative research initiative develops semantic-aware code generation techniques for Large Language Models (LLMs) to improve the quality and reliability of...
- Federal Grant Award Summary Carnegie Mellon University received a $150,000 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded August 15, 2025, with a completion date of July 31, 2028. The grant supports fundamental research addressing probabilistic and geometric themes in combinatorics, with three primary research directions: (1) enabling statistical inference for probability...
Federal Grant Award Summary Carnegie Mellon University received a $1.395 million Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award, effective April 1, 2026, through March 31, 2031, supports the development of the Framework for Advanced (Multi)linear Infrastructure in Engineering and Science (FAMLIES). This collaborative research initiative delivers an adaptable, open-source software framework for matrix and tensor computations, targeting the entire high-performance computing hardware stack with vertically integrated software layers. The framework is designed to support critical applications in drug discovery, quantum computing development, and artificial intelligence architectures while reducing computational resource demands and energy costs. The FAMLIES project advances scientific computing infrastructure by building upon four decades of dense linear algebra software library development while introducing modernized approaches and flexible interfaces. The deliverable framework conveniently supports existing and future computational tools, lowers barriers to entry for researchers, and facilitates workforce development in computational and data science fields. By addressing the computational bottlenecks inherent in machine learning, artificial intelligence, and scientific discovery, the project enables broader innovation across engineering and science disciplines while maintaining accessibility through open-source licensing and integration with cutting-edge research cyberinfrastructure.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.4m | 3/26/26 |