Project Grant 2542272
- Federal Grant Award Summary Carnegie Mellon University received a $232,159 CAREER award from the National Science Foundation's Division of Information and Intelligent Systems (Computer and Information Science and Engineering program, CFDA 47.070) effective May 1, 2025, through April 30, 2030. The project delivers foundational research and development of environment optimization frameworks and methodologies for large-scale multi-agent coordination in autonomous systems. Specifically, the award...
- 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 $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 The National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) awarded a Project Grant of $364,815 to University of California, Berkeley on April 15, 2026, with completion scheduled for March 31, 2031. This CAREER award supports the development of rigorous mathematical foundations and algorithms for nonconvex nonsmooth optimization problems—a fundamental challenge in modern artificial intelligence and complex decision-making...
- Federal Project Grant Award Summary Carnegie Mellon University received a $348,956 project grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) effective June 15, 2025, with completion targeted for May 31, 2030. This CAREER award supports foundational research to develop perception systems capable of understanding actionable 3D environments from 2D visual input. The project will produce computational approaches and...
- Federal Grant Award Summary Carnegie Mellon 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), awarded July 1, 2025, with completion targeted for June 30, 2030. This CAREER award supports fundamental research on safety, human alignment, and interaction-awareness in autonomous control systems operating across multiple domains including transportation,...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Computing and Communication Foundations, awarded a five-year CAREER grant totaling $530,283 to the University of Michigan, effective May 1, 2026 through April 30, 2031, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This project grant supports fundamental research advancing the theoretical and algorithmic understanding of paths in graphs—a critical computational problem with...
- 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 $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 Grant Award Summary Carnegie Mellon University received a $383,675 Project Grant award on June 15, 2025, from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award supports a five-year research initiative (completion date: May 31, 2030) titled "CAREER: Worker-Centered Design: Building Worker Voice into the Present and Future of Work." The project...
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 delivers research advances in two primary areas: optimization methods using interior point frameworks for minimum-cost flow and graph problems with applications to logistics, telecommunications, and artificial intelligence; and analytical techniques investigating correlations in high-dimensional functions and constraint satisfaction problems with implications for algorithms and complexity theory foundations. In addition to research deliverables, the award funds significant education and workforce development activities including course design, student mentoring, workshops, summer schools, and outreach initiatives to broaden access to advanced mathematics and computer science concepts. The project emphasizes bridging combinatorial and analytic techniques to address open problems in algorithms and complexity theory, with specific objectives to lower iteration complexity in optimization methods, extend nearly linear-time computational approaches to broader graph settings, and develop dynamic data structures for applications such as shortest path computation and cycle detection.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $331.7k | 3/25/26 |