The National Science Foundation (NSF) awarded a $224,672 Project Grant on August 15, 2023 to Florida State University (FSU) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports the project "Collaborative Research: SHF: Medium: Towards Harmonious Federated Intelligence in Heterogeneous Edge Computing via Data Migration." The goal is to develop a framework to enable federated learning with high accuracy and efficiency in heterogeneous...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program award of $122,705 to Clemson University provides funding to develop novel approaches for federated on-device intelligence in Internet of Things (IoT) systems. The project focuses on two key challenges: (1) enabling federated knowledge sharing among resource-constrained and heterogeneous IoT devices without requiring private data, and (2) enabling federated domain adaptation with...
This $500,000 National Science Foundation Project Grant through the Integrative Activities program (CFDA 47.083) funds research at Auburn University towards efficient and fast hierarchical federated learning in heterogeneous wireless edge networks. The university will conduct research over five years to develop fundamental understandings and adaptive, efficient algorithms and schemes for wireless hierarchical federated learning. This addresses challenges from non-uniform device configurations,...
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...
This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $100,000 to develop enabling technologies for integrating distributed intelligence into the network edge to support next-generation smart applications. The project will focus on techniques for the life cycle of distributed intelligence, including data curation, decentralized learning/fine-tuning, and distributed inferencing, optimized for...
This $381,264 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the University of Florida to develop hardware-efficient artificial intelligence techniques for federated learning across diverse Internet of Things devices. Over a three-year period ending September 2025, the research team will work to enable quantization and pruning of neural networks in a way that accounts for the varied computational...
This $499,861 National Science Foundation project grant under the Computer and Information Science and Engineering program (CFDA 47.070) supports the development of real-time, scalable and secure collaborative intelligence capabilities at the edge. Wayne State University is the primary awardee and will work with sub-awardee University of Delaware to implement collaborative learning algorithms enabling distributed, privacy-preserving training across edge devices for multi-target tracking...
This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering (CFDA 47.070) program, provides $274,648 to Clemson University to develop heterogeneous architectures for collaborative machine learning. The research aims to address key challenges in efficiency, adaptivity, and privacy preservation when deploying collaborative machine learning models across diverse hardware platforms. The project will design specialized neural network...
The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a $360,000 Project Grant to Carnegie Mellon University for the "Federated Optimization Over Bandwidth-Limited Heterogeneous Networks" research program. The goal of this 3-year (9/1/2023 - 8/31/2026) project is to develop a federated optimization framework for learning and decision-making by designing communication-efficient, computation-scalable, and privacy-preserving algorithms that...
This $173,754 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop an innovative privacy-preserving federated learning (FL) framework suitable for heterogeneous edge devices. The key objectives are to: 1) enable tailored device-specific models to mitigate biases and enhance performance across diverse computational capabilities and data distributions, 2) utilize differential privacy...