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 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award, with a total funding of $174,770, supports the development of an adaptive, federated, continuous learning system that uses a novel federated, semi-supervised learning framework. This framework aims to retrain deep neural network models on distributed, unlabeled, heterogeneous data from edge devices, while leveraging explainable AI techniques to expedite local training. The...
This $237,859 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research to enhance cybersecurity and privacy techniques for the integration of the Internet of Things (IoT) and Artificial Intelligence, known as the Artificial Internet of Things (AIoT). The key research tasks under this three-year project include: 1) Building a joint research testbed for integrating AI and IoT, 2) Investigating data...
This federal Project Grant, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to design and develop a secure and efficient decentralized federated learning (DFL) system. The $380,667 grant, awarded on August 15, 2024, will fund research to address communication, computation, and security issues in DFL, which enables training of data-hungry machine learning models on local devices without sharing raw data. The...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with CFDA number 47.070, provides $131,520 to William Marsh Rice University in Houston, Texas. The funding will advance research on decentralized learning methods, which can improve data privacy, reduce communication bottlenecks, and enhance performance in areas like healthcare monitoring and environmental data processing. The project aims to develop novel...
This National Science Foundation (NSF) Project Grant award, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $159,979 to the New York Institute of Technology (NYIT) from September 1, 2023 to August 31, 2026. The grant supports the development of transformative machine learning and data analytics technologies to enable efficient and robust artificial intelligence (AI)-based applications on resource-constrained edge computing devices such as IoT sensors,...
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 Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to develop a distributed learning system called "United Learning" that enables efficient data sharing and model training across heterogeneous computing devices, including personal computers, smartphones, and IoT devices. The key products and services to be delivered under this $175,000 award include: 1) Designing...
This National Science Foundation Project Grant of $299,181 supports research and education efforts toward opportunistic, fast, and robust in-cache artificial intelligence acceleration at the edge for Internet of Things devices. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the award to New Jersey Institute of Technology from January 1, 2023 to December 31, 2025 aims to design and deploy new hardware-oriented AI algorithms for efficient image...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $145,830 to Old Dominion University Research Foundation (Odurf) to develop a secure and decentralized AI learning system for heterogeneous IoT networks. The project aims to design a novel distributed learning method that can effectively utilize diverse data types from various IoT devices without relying on a central server. It will also analyze system vulnerabilities, develop attack and defense mechanisms, and assess the reliability of the decentralized learning approach. This work lays the groundwork for more secure and efficient decentralized AI applications in areas like smart cities, smart homes, and mobile health. The award period runs from August 1, 2024 to June 30, 2025. No sub-awards are planned under this grant.