Project Grant 2513798
- Federal Grant Award Summary The University of Rochester received a $108,936 Project Grant award from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective May 1, 2026, with completion targeted for April 30, 2029. This collaborative research initiative will develop DIFFAI, an open-access platform designed to host experimental powder X-ray diffraction (XRD) data and associated...
- Federal Project Grant Award Summary Columbia University received a $575,000 project grant from the National Science Foundation's (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), awarded August 1, 2025, with completion targeted for July 31, 2028. This collaborative research initiative develops theoretical foundations and algorithmic methods to improve data quality in machine learning systems through...
- Federal Grant Award Summary The National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) awarded $500,000 to The Research Foundation For The State University of New York on September 1, 2025, for a four-year implementation project (through August 31, 2029) titled "CyberTraining: Implementation: Small: Modeling Quantum Dynamics of Excited States in Materials in the Era of Machine Learning." The project addresses a critical national...
- Federal Grant Award Summary The National Science Foundation's Division of Materials Research awarded a $1.5 million Project Grant to the University of Texas at Austin on October 1, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop MATCSSI 2.0, a cloud-integrated platform that democratizes access to advanced many-body electronic structure computational methods. The project, which extends through September 30, 2028, addresses the mathematical complexity and...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded Columbia University $155,000 on August 1, 2025, under the Mathematical and Physical Sciences (CFDA 47.049) program to develop adaptive data integration methodologies for heterogeneous datasets. Over the three-year project period (August 1, 2025 – July 31, 2028), the award will deliver three primary research thrusts: transfer learning methods for integrating multi-source samples...
- Federal Grant Award Summary Columbia University received a $163,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for collaborative research on the emergence of features in modern machine learning systems. The award, effective October 1, 2025, through September 30, 2028, supports the development of mathematical foundations for understanding how artificial intelligence (AI) models represent...
- Federal Grant Award Summary Fordham University received a $393,021 Project Grant award dated February 15, 2026, from the National Science Foundation's Division of Materials Research under the Mathematical and Physical Sciences program (CFDA 47.049). The collaborative research project, which extends through January 31, 2029, focuses on accelerated discovery of lead-free metal halide perovskitoids through automation and artificial intelligence (AI). Key deliverables include development of...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a $3.0 million Project Grant (CFDA 47.041 - Engineering program) to Columbia University, with performance beginning October 1, 2025 and concluding September 30, 2028. This collaborative research initiative, conducted in partnership with the University of Michigan, develops steady-state Floquet engineering platforms that utilize continuous-wave electromagnetic...
- This Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of an open-source high-fidelity materials database using the DFT+DMFT method. The $149,983 award to Rutgers, The State University, aims to overcome the limitations of existing materials databases built using basic Density Functional Theory (DFT) by incorporating the more precise...
- Federal Project Grant Award Summary New York University received a $300,000 Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025 through September 30, 2028. The HS-SPECTRA (Hyperspectral Standardizing and Sharing Possibilities for Urban Conditions Through Toolkits, Resources and Archiving) project will develop and extend community involvement...
The National Science Foundation's Office of Advanced Cyberinfrastructure awarded Columbia University a $191,000 Project Grant (CFDA 47.070: Computer and Information Science and Engineering) effective May 1, 2026, through April 30, 2029, to develop DIFFAI (Diffraction Database and Intelligent Analysis), an open-access platform for experimental powder diffraction data. The project delivers three primary products: a centralized, community-driven database hosting experimental X-ray diffraction (XRD) patterns with standardized metadata; artificial intelligence (AI) tools for automated analysis of diffraction data; and comprehensive training and outreach programs including student education and community workshops. These integrated services are designed to address the current fragmentation of diffraction data across publications and local storage systems, enabling enhanced structure determination of complex materials including quantum materials. DIFFAI aims to democratize access to high-quality experimental diffraction data and machine learning models, thereby accelerating materials discovery and establishing global standards for data sharing and analysis. By making diffraction data findable, accessible, and reusable consistent with FAIR principles, the platform facilitates collaboration within the global research community while lowering barriers to materials characterization. The project advances foundational cyberinfrastructure capabilities that support materials science research with applications spanning microelectronics, energy storage, and national defense systems.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $191.0k | 4/2/26 |