Project Grant FA23862314057

This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program provides $366,883 to the University of Massachusetts Lowell (UML) to develop a robust continual representation learning model. The project aims to address challenges in representation learning techniques for analyzing diverse, streaming, and sensitive data collected from multiple sources, such as cybersecurity, industry, finance, and scientific applications. The key...

The National Science Foundation (NSF) awarded a $175,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of North Carolina at Charlotte. The project, titled "CRII: CSR: ENABLING ON-DEVICE CONTINUAL LEARNING THROUGH ENHANCING EFFICIENCY OF COMPUTING, MEMORY, AND DATA", aims to develop an efficient on-device continual learning framework that can incrementally learn new knowledge without forgetting prior learnt knowledge, while...

This $1.7 million National Science Foundation project grant supports research at West Virginia University and the University of Arkansas, Fayetteville to develop unsupervised continual learning algorithms inspired by neuroplasticity mechanisms observed in electric fish. Funded through NSF's Engineering Directorate (ENG) under the Established Program to Stimulate Competitive Research and Emerging Frontiers in Research and Innovation Brain-Inspired Dynamics for Engineering Energy-Efficient...

This three-year, $399,754 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of lifelong learning algorithms using hyperdimensional computing. The University of California, Berkeley will advance approaches for artificial intelligence systems to handle changing environments through building algorithms for fundamental statistical primitives like similarity search, density estimation, and...

This National Science Foundation (NSF) grant award under the Computer and Information Science and Engineering program (CFDA 47.070) provides $250,000 over 3 years to Northeastern University, a private non-profit research university based in Boston, MA, to develop advanced techniques for continual online learning on energy-constrained edge computing devices. The key products and services to be delivered through this research project include: (1) an attention-guided smart layer freezing approach...

This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) in the amount of $544,381 provides funding to the Regents of the University of Minnesota to develop a principled framework for continual learning, consisting of novel theoretical insights and practical algorithmic designs. The overarching goal is to pioneer methodological advancements in continual learning to empower autonomous machine learners navigating dynamic data environments. The research will...

The National Science Foundation awarded a $525,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) to support research investigating energy-efficient persistent learning-in-memory with quantum tunneling dynamic synapses from October 1, 2022 to September 30, 2025. The award will fund the development of novel learning hardware and software tools to significantly improve the energy efficiency of artificial...

The National Science Foundation awarded a $245,043 Project Grant to Carnegie Mellon University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The five-year award will support research towards theoretical foundations of neural network-based representation learning. Specifically, the awardee will build a comprehensive theory for new neural network representation learning techniques. This includes characterizing statistical properties of...

This four-year $800,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) will support research at the University of California, Los Angeles (UCLA) to develop theoretical tools for understanding deep neural networks (DNNs). The research aims to identify common themes in how artificial and biological systems like the human brain learn. It will investigate the hypothesis that DNNs succeed when learning tasks exhibit...

This $618,159 National Science Foundation project grant supports research into developing energy-efficient hardware and software for machine learning and artificial intelligence systems. Funded under the Computer and Information Science and Engineering program, the award supports The Washington University in investigating frameworks using quantum-tunneling dynamic-analog memory devices and novel online learning algorithms. Specific objectives include exploring Fowler-Nordheim dynamic analog...