Project Grant 2551408
- Virginia Commonwealth University was awarded a $500,000 Project Grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research to develop integrated prediction of intrinsic disorder and disorder functions using modular multi-label deep learning. The project aims to advance computational methods for characterizing intrinsically...
- This $248,508 National Science Foundation project grant supports the development of computational tools and a database for modeling protein-protein and protein-nucleic acid interactions involving intrinsically disordered regions. Funded under the Biological Sciences program (CFDA 47.074), key products include high-accuracy prediction of binding regions within disordered sequences using multi-task deep learning models; identification of partner molecules for these regions; and structure...
- Federal Project Grant Award Summary Virginia Commonwealth University received a $600,000 Project Grant from the National Science Foundation's Office of Integrative Activities (CFDA 47.083) awarded January 1, 2026, with completion scheduled for December 31, 2028. The LLMDAL (LLM-Driven Data Labeling) project leverages large language models (LLMs) and network data from the AMLight International Research and Education Network—maintained by sub-awardee Florida International University—to...
- Federal Project Grant Award Summary The University of Virginia received a $600,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), awarded October 1, 2025, with completion targeted for September 30, 2028. This research initiative develops constrained generative artificial intelligence (AI) models that integrate physical principles and safety constraints...
- Federal Grant Award Summary Virginia Commonwealth University received a $307,000 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award, effective September 1, 2025, through August 31, 2029, supports collaborative research on a Processor in Memory Architecture based on Topological Electronics (PRIMATE). The project will design, simulate,...
- Federal Project Grant Award Summary The University of Virginia received a $300,000 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (Computer and Information Science and Engineering program, CFDA 47.070) effective August 1, 2025, through July 31, 2028. This research initiative develops methodologies to optimize knowledge utilization in Large Language Models (LLMs) and foundation models to enhance their capability for generating novel...
- Federal Grant Award Summary The University of Virginia received a $815,002 Project Grant award from the National Science Foundation's Division of Biological Infrastructure under the Biological Sciences program (CFDA 47.074), effective August 15, 2026 through July 31, 2029. The award supports development of an integrated graph machine learning platform designed to accelerate peptide discovery and design by leveraging both two-dimensional topological and three-dimensional geometric structural...
- Federal Project Grant Summary Virginia Polytechnic Institute & State University (Virginia Tech) received a $270,000 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), effective August 1, 2025, with completion targeted for July 31, 2028. This collaborative research initiative addresses critical limitations in current large language models (LLMs) by developing...
- Federal Grant Award Summary Virginia Commonwealth University received a $551,083 CAREER Project Grant from the National Science Foundation (NSF) Directorate for Engineering, Division of Chemical, Bioengineering, Environmental, and Transport Systems (CFDA 47.041), effective September 1, 2026 through August 31, 2031. The award funds research to develop light-controlled enzymes for sustainable biomanufacturing applications. The primary deliverables include engineering light-activated protein...
- Federal Project Grant Award Summary The National Science Foundation (NSF), Division of Materials Research, awarded Virginia Polytechnic Institute & State University a $440,018 Project Grant (CFDA 47.049, Mathematical and Physical Sciences) effective July 1, 2026, through June 30, 2031, to develop genetically programmable protein nanofibers for mechanically tunable engineered living materials (ELMs). The research employs rational design and artificial intelligence methodologies to enable...
Federal Project Grant Summary Virginia Commonwealth University received a $593,556 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070) to develop and validate a novel contrastive dual-head transformer neural network architecture for protein bioinformatics applications. The award, issued July 15, 2026, with a completion date of June 30, 2029, will deliver a taxonomy-wide intrinsic disorder predictor (TONIC) capable of accurately modeling multiple sequence populations and identifying functions of intrinsically disordered proteins—a critical gap in computational protein discovery where existing tools like AlphaFold address structured proteins but fail to annotate disordered protein functions. The primary deliverables include the design, implementation, empirical validation, and public release of the transformer neural network architecture optimized for protein sequence analysis across flexible linkers and molecular interactions. VCU will disseminate this architecture freely to the scientific community to enable development of advanced computational tools for functional protein annotation at scale, with anticipated indirect impacts across bioinformatics, protein science, structural biology, chemistry, and biophysics disciplines. The innovative network will be applied to multiple areas of protein research and positioned as a general-purpose tool to accelerate scientific discovery across computational biology domains.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $593.6k | 7/11/26 |