This Project Grant award, funded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports the "ByteBoost 2.0" initiative. The $207,761 award will enable a community-driven training platform to empower computational researchers and educators with advanced cyberinfrastructure (CI) technologies, including artificial intelligence (AI) and data-enabled scientific tools. The program will provide a series of online...
This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports the "ByteBoost 2.0" initiative at Texas A&M University. The $583,967 award will fund a community-driven training platform to empower computational researchers and educators with novel, cutting-edge cyberinfrastructure (CI) technologies, including artificial intelligence (AI) and advanced computing capabilities. The...
This Project Grant award, totaling $295,536, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant aims to enhance the role of campus champions, research computing facilitators at academic institutions, by equipping them to promote access to advanced artificial intelligence (AI) resources and foster collaborations. It addresses barriers in AI research by connecting under-resourced and minority-serving...
The National Science Foundation (NSF) awarded a $280,000 Project Grant through its STEM Education (CFDA 47.076) program to develop and evaluate a Comprehensive Personalized Programming Practice Environment (C-3PE) that utilizes artificial intelligence (AI) to enhance computer science education. The collaborative project, led by Carnegie Mellon University in partnership with the University of Pittsburgh, University of Massachusetts, and North Carolina State University, aims to provide...
The National Science Foundation (NSF) awarded Carnegie Mellon University a $647,613 Project Grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to fund the "YINZERNET: A MULTI-SITE DATA AND AI DRIVEN RESEARCH NETWORK" project. This award will support the development of a high-performance networking infrastructure that eliminates data movement and computing bottlenecks, enhancing interdisciplinary research collaborations between the University...
This $299,998 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will support collaborative research at Carnegie Mellon University to develop new big data algorithms that are robust to adversarial input. The key focus areas include: 1) adversarial robustness in black-box and white-box streaming settings, and 2) adaptive data analysis with bounded space. The research team will also explore emerging attack...
The National Science Foundation (NSF) awarded a $268,428 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Colorado. The grant, titled "EAGER: AI for All: Engaging the Public with Collaborative Student-Led AI Education," will engage interdisciplinary groups of college students in creating educational artificial intelligence (AI) content for social media. The goal is to cultivate communication skills in undergraduates and...
This $295,000 Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to train the future research workforce to develop and use AI-based cloud cybersecurity solutions that are fair, ethical, and unbiased. The key products and services to be delivered under this 3-year award, which begins on August 1, 2024, include: Developing and integrating seven advanced experiential learning modules, referred to...
The National Science Foundation (NSF) awarded a $406,004 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Carnegie Mellon University (CMU). The goal of this 4-year project is to develop new resource allocation policies that enable efficient and timely training of machine learning models by leveraging parallelizable computing resources. The research will focus on modeling the unique characteristics of machine learning training workloads, such as...
This $389,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports collaborative research at Carnegie Mellon University (CMU) to develop provably correct, high-performance computational methods for scientific applications involving complex multi-dimensional data structures like tensors. The project aims to create new notations, algorithms, and software tools that can automatically generate...