Project Grant 2544101
- Federal Project Grant Award Summary Massachusetts Institute of Technology received a $240,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems (CISE program, CFDA 47.070) awarded June 15, 2025, with completion scheduled for May 31, 2030. This CAREER award funds the development of advanced computer vision (CV) methodologies to enable global-scale, near-real-time biodiversity monitoring. The research addresses critical limitations in current CV...
- Federal Project Grant Award Summary Arizona State University was awarded a $344,819 CAREER grant effective July 1, 2025, through June 30, 2030, by the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This project grant supports fundamental machine learning research aimed at advancing analytical capabilities for satellite remote sensing data. The research will deliver four primary...
- Federal Project Grant Award Summary Massachusetts Institute of Technology (MIT) received a $360,000 National Science Foundation (NSF) CAREER award under Computer and Information Science and Engineering (CFDA 47.070) beginning July 1, 2026, and concluding June 30, 2031. The award funds research and development of a self-supervised video representation learning framework designed to enable artificial intelligence systems to extract action-relevant knowledge directly from raw video and sensor...
- Federal Project Grant Award Summary Funding Agency: National Science Foundation, Office of Integrative Activities Program: Geosciences (CFDA 47.050) Award Amount: $325,000 Award Date: October 1, 2025 Performance Period: October 1, 2025 – September 30, 2028 Awardee: Massachusetts Institute of Technology (Cambridge, MA) This collaborative research project develops advanced artificial intelligence (AI) tools and improved Earth System Model (ESM) parameterizations to address critical limitations...
- Federal Grant Award Summary Massachusetts Institute of Technology received a $497,026 Project Grant from the National Science Foundation (NSF) Office of Integrative Activities under the Geosciences program (CFDA 47.050), awarded October 1, 2025, with completion targeted for September 30, 2028. The award funds collaborative research to develop the first multiscale artificial intelligence (AI) ocean emulator capable of spanning submesoscales to large-scale ocean flows. The primary deliverable is a...
- The Massachusetts Institute of Technology (MIT) received a $1.2 million project grant award from the National Science Foundation Office of Advanced Cyberinfrastructure to support research activities under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will fund a collaborative research project between Aug 1, 2021 and Jul 31, 2025 to develop frameworks that converge Bayesian inverse methods and scientific machine learning in Earth system models...
- Federal Grant Award Summary The National Science Foundation's Office of Integrative Activities has awarded Massachusetts Institute of Technology $297,985 under the Geosciences Program (CFDA 47.050) to enhance the accessibility and utility of the Madrigal database, a distributed data system for space physics research. The project, which runs from August 1, 2025, through July 31, 2027, will deliver three primary products: an artificial intelligence-powered virtual assistant using...
- Federal Grant Award Summary Massachusetts Institute of Technology received a $280,247 Project Grant from the National Science Foundation's Office of Integrative Activities under the Geosciences program (CFDA 47.050) awarded October 1, 2025, with completion targeted for September 30, 2028. This collaborative research initiative delivers foundational scientific products and datasets addressing small-scale turbulence dynamics at the air-sea boundary layer. The project integrates high-resolution...
- Federal Grant Award Summary The National Science Foundation's Division of Computer and Network Systems awarded a $720,000 Project Grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to Massachusetts Institute of Technology, with performance in Cambridge, Massachusetts. This collaborative research initiative, executed in partnership with the University of Washington and spanning August 1, 2025 through July 31, 2028, delivers machine learning-based...
- Federal Project Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a $503,740 CAREER grant to Stanford University beginning August 1, 2025, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The project develops probabilistic machine learning models and computational tools designed to analyze spatiotemporal data with scalability and accuracy improvements. The core deliverables include modular...
The National Science Foundation's Office of Advanced Cyberinfrastructure (OAC) awarded a CAREER grant of $432,737 to the Massachusetts Institute of Technology (Cambridge, MA) on July 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070). The five-year project, concluding June 30, 2031, will develop foundation models and machine learning approaches for large-scale earth observation satellite imagery analysis. The research focuses on establishing scaling laws and generalization boundaries for earth observation foundation models, characterizing how model performance varies with dataset size, model size, land cover diversity, and multi-modal satellite inputs. The project will also develop novel pretraining strategies that leverage noisy but structured geospatial information, thereby reducing dependence on expensive expert-labeled training data and broadening access to earth observation technologies across scientific domains and data-scarce regions. The award includes integrated educational components that will train students at the intersection of machine learning and earth observation through development of a new course, open-source learning materials, and undergraduate research mentoring opportunities. By advancing foundation model capabilities for satellite imagery interpretation, this research aims to improve monitoring and analysis of agriculture, infrastructure, natural disasters, air quality, and ecosystems globally, while simultaneously reducing the technical and financial barriers to applying advanced machine learning techniques to earth observation applications.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $432.7k | 6/30/26 |