Project Grant 2602595
- The National Science Foundation (NSF) awarded a $116,552 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Riverside (UC Riverside) to develop open-source cyberinfrastructure for publishing and reusing minimally compressed measurement data from large physics experiments. The project aims to build tools that enable measurements directly on uncompressed or minimally compressed data, addressing limitations in current...
- This $198,234 Project Grant awarded by the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure (CFDA 47.070 - Computer and Information Science and Engineering) supports research and development of advanced lossy data compression techniques that preserve topological features in scientific data. The project aims to develop algorithms to effectively reduce the size of large-scale scientific simulation data, such as from fusion and climate modeling, while preserving critical...
- This $299,999 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a novel learning-driven framework to mitigate artifacts produced by scientific data compressors. The project aims to improve the integrity and quality of lossy-compressed scientific data, facilitating efficient data storage, transmission, and analytics across disciplines like climatology, cosmology, and fusion energy...
- This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a performance period from July 1, 2025 to June 30, 2028, will support a collaborative research project to develop a cyberinfrastructure that seamlessly integrates lossy data compression into deep learning pipelines for scientific applications. The goal is to reduce memory usage and communication overhead, enabling AI-driven scientific applications...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $272,992 will support a collaborative research project at Texas State University titled "SCIOPT: Toward Certifiable Compression-Aware SCIML Systems." The project aims to develop techniques to reduce the volume of data exchanged in high-performance scientific computing and scientific machine learning (SCIML) applications without...
- This $819,000 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) will fund a collaborative research project titled "SCIOPT: Toward Certifiable Compression-Aware SCIML Systems" at the University of Utah. The project aims to develop techniques to reduce the volume of data exchanged in high-performance scientific simulations and scientific machine learning (SCIML) applications without sacrificing accuracy. Key...
- This $240,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a user-friendly, high-performance, and portable GPU-accelerated data reduction cyberinfrastructure called the Scientific GPU Compression Cyberinfrastructure (SGCC). The University of Chicago, the award recipient, will port, extend, and optimize multiple existing GPU-based data compression capabilities, including error-bounded...
- The National Science Foundation (NSF) awarded a $299,999 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Chicago. The grant, titled "COLLABORATIVE RESEARCH: ELEMENTS: A CYBERINFRASTRUCTURE FOR SEAMLESSLY INTEGRATING LOSSY COMPRESSION INTO NEURAL NETWORKS FOR SCIENTIFIC APPLICATIONS," aims to develop a cyberinfrastructure that seamlessly and adaptively integrates lossy data compression techniques into deep learning...
- The National Science Foundation (NSF) awarded a $299,354 Project Grant under the Computer and Information Science and Engineering (CISE) program to The University of Kentucky Research Foundation. This 3-year collaborative research project aims to develop a novel learning-driven framework to mitigate compression artifacts in scientific data compressors. The research will investigate and characterize compression artifacts, design deep learning models to address artifact mitigation, and validate...
- This $240,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support fundamental research on unsupervised learning and nonlinear dimension reduction. The project aims to develop new statistical frameworks and cutting-edge techniques for analyzing complex, high-dimensional scientific datasets, ranging from single-cell RNA sequencing to astronomy data. Key deliverables include: (1) new empirical Bayes methods for...
This $95,254 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of open-source cyberinfrastructure to publish and reuse minimally compressed measurement data for physics research and education. The project aims to address limitations in statistical methods and exchange platforms that compress complex reaction rate data, hindering scientific discovery and data reuse. By leveraging recent advancements in machine learning, the researchers will create tools to enable direct measurements from un- or minimally compressed data, extending the practical lifetime of experimental facilities and enabling high-quality analyses beyond the initial data collection period. The award supports a collaborative effort between researchers at The Leland Stanford Junior University, with a performance period from November 1, 2025 to August 31, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $95.3k | 11/21/25 |