Project Grant 2537189
- This federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $240,000 to Yale University to conduct research on 2-stage stochastic wireless system optimization. The project aims to develop a new methodological framework for jointly managing short-term and long-term decision variables in wireless systems, such as bandwidth, power, and spectrum allocation, to optimize performance. The research addresses technical challenges in algorithm...
- This $348,573 project grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering federal grant program (CFDA 47.041), will fund research at North Carolina State University from September 2022 through August 2025. The university will advance the frontiers of federated learning through exploring tradeoffs among learning performance, communication efficiency, privacy protection, and system robustness under a generalized...
- The National Science Foundation awarded Yale University a $406,081 project grant under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research from October 2021 through September 2024 to advance learning techniques for next generation wireless networks. Specifically, the university will conduct work on learning to network the edge in next generation wireless networks. The Computer and Information Science and Engineering program aims to...
- This $249,999 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports the development of a novel communication-efficient hierarchical distributed optimization framework that integrates optimization, communication, and machine learning. The core innovation is to sample and learn models of networked agents' behaviors, then use these models to predict agents' responses and enable informed decision-making while minimizing unnecessary...
- Lehigh University received a $175,000 Project Grant award from the National Science Foundation under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to conduct research towards improving the handling of heterogeneity and personalization in federated learning. The University will develop mathematical models and efficient algorithms to address issues in heterogeneous federated learning caused by data and device diversity. Researchers will design advanced...
- The Project Grant award of $131,520 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to advance decentralized learning methods that can improve data privacy, reduce communication bottlenecks, and enhance learning performance in modern, distributed data systems. The key research thrusts of this 5-year project (4/15/2025 - 3/31/2030) include developing finite-time aggregation networks for faster convergence in decentralized...
- This Project Grant award from the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) provides $196,737 to Yale University to develop theoretical and algorithmic foundations for solving nonlinear inverse problems. The project aims to advance the state-of-the-art in optimization methods and algorithms for efficiently and accurately making sense of large-scale sensing and imaging data beyond classical linear models. Key objectives include designing scalable algorithms...
- The National Science Foundation (NSF) awarded a $498,229 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to Yale University. The grant will fund research to develop new mathematical and machine learning techniques for analyzing complex, high-dimensional biomedical data such as single-cell sequencing and gene regulatory networks. Key research thrusts include creating data geometric features and neural network models to characterize point cloud data, preserving...
- Yale University was awarded a $250,000 Project Grant from the National Science Foundation under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support research titled "COLLABORATIVE RESEARCH: SWIFT: SHIELD: A SOFTWARE-HARDWARE APPROACH FOR SPECTRUM COEXISTENCE WITH RAPID INTERFERER LEARNING, DETECTION, AND MITIGATION" from October 1, 2021 through September 30, 2024. The research aims to develop a software-hardware system to...
- The National Science Foundation (NSF) awarded a $513,998 Project Grant under the Engineering Program (CFDA 47.041) to North Carolina Agricultural and Technical State University (NC A&T) for the "CAREER: ADVANCING FEDERATED LEARNING: INCENTIVIZING PRIVACY-PRESERVING COLLABORATIVE LEARNING IN DYNAMIC ENVIRONMENTS" project. The project aims to address key challenges in federated learning, a method for collaborative machine learning model training without sharing private data....
This $316,074 federal Project Grant award was provided by the National Science Foundation (NSF) Engineering program (CFDA 47.041) to Yale University. The grant, effective July 1, 2025 through August 31, 2026, aims to develop a federated optimization framework for learning and decision-making in bandwidth-limited heterogeneous networks. The research will design communication-efficient, computation-scalable, and privacy-preserving algorithms that converge over heterogeneous data and computing environments. Leveraging insights from machine learning, optimization theory, signal processing, and differential privacy, the research program will provide new theoretical and algorithmic tools to enable heterogeneity-embracing and privacy-preserving learning and decision-making in federated environments under bandwidth constraints. The project will also integrate education and workforce development through new courses, student mentoring, and disseminating research outcomes.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $316.1k | 9/2/25 |