Project Grant 2206341
Award Date
9/1/22
Completion Date
8/31/25
Dollars Obligated
$135K
Federal Agency
Division of Astronomical Sciences
Federal Grant Program
47.049
Assistance Type
Project Grant
Place of Performance
Baltimore, MD 21218, USA
Similar Awards
This three-year project grant from the National Science Foundation Division of Astronomical Sciences totals $360,645 to develop new statistical and machine learning methods and software to improve the detection, characterization, and classification of astrophysical objects using multi-epoch imaging survey data. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), key products include new algorithms for classifying variable and transient objects based on light curves...
This three-year, $110,972 Project Grant from the National Science Foundation's Division of Astronomical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of new statistical and machine learning methods and software to improve the detection, characterization, and classification of astrophysical objects using multi-epoch imaging survey data. The California Institute of Technology will apply innovative algorithms to optimize the discovery...
The National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences awarded a $228,435 Project Grant to The Johns Hopkins University to develop a toolkit of understandable machine learning (ML) methods for interpreting detailed optical galaxy surveys from the Rubin Observatory and Dark Energy Spectroscopic Instrument. This 3-year award, running from September 1, 2023 to August 31, 2026, aims to: 1) produce a statistical census of cosmological information at small scales,...
The National Science Foundation (NSF) awarded a $207,876 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to President and Fellows of Harvard College. This grant will support the development, testing, and application of machine learning (ML) algorithms and pipelines for the photometric classification of optical transients from current and future astronomical surveys. The key products and services to be delivered under this project include: (i) combining...
This Project Grant award from the National Science Foundation Division of Astronomical Sciences provides $403,383 to President And Fellows Of Harvard College for research and application development under the Mathematical and Physical Sciences program (CFDA 47.049). Specifically, the award supports collaborative research to develop machine learning techniques for classifying optical transients detected through astronomical observation. The research is being conducted between September 2021 and...
This $374,699 four-year Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support collaborative research by investigators at Louisiana State University, Harvard University, University of Minnesota-Twin Cities, and University of Maryland, College Park. The research aims to improve understanding of explosive transient astronomical events, which occur at the extremes of physics, by combining observations from the Vera C....
This $355,665 project grant from the National Science Foundation's Mathematical and Physical Sciences program will fund research at The Johns Hopkins University to improve characterization of Type IA supernova host galaxy properties. The university will compile an extensive multi-wavelength dataset leveraging existing optical data and upcoming infrared archives to recover star formation histories through non-parametric fitting and determine stellar masses and formation rates for supernova host...
This Project Grant award from the National Science Foundation's Division of Astronomical Sciences provides $587,441 to the University of Delaware over 3 years, from August 2023 to July 2026. The purpose is to adapt time-domain data analysis tools previously used in other scientific fields for application in astronomy, specifically for searches of Earth-like exoplanets around distant stars. The key deliverables include: Developing new variance-suppressing power spectrum estimators, like the...
This $238,354 Project Grant awarded by the National Science Foundation (NSF) Division of Astronomical Sciences under the Mathematical and Physical Sciences grant program (CFDA 47.049) will fund collaborative research to develop improved image processing software for high-contrast imaging of exoplanets. The project aims to enable more sensitive detection and characterization of exoplanets by fully utilizing data from the wavefront sensors in modern high-contrast imaging systems. The software will...
This $586,924 National Science Foundation project grant supports the development of scalable and efficient astronomical data processing software among distributed observatories. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the University of Virginia team will design system software focusing on performance measurement and analysis of data processing jobs run on the National Radio Astronomy Observatory's Common Astronomy Software Applications and machine/deep learning...