A Foundational Model for Extragalactic Spectroscopy: Combining Transformer-Based Deep Lear — NSF Award to Rochester Institute of T
Spectroscopic observations of galaxies contain critical information about their physical properties, and modern large spectroscopic surveys of galaxies are producing a plethora of data. Given the size of these datasets, traditional data analysis methods are prohibitively time consuming. The Principal Investigator (PI)
| Award title | A Foundational Model for Extragalactic Spectroscopy: Combining Transformer-Based Deep Lear |
|---|---|
| Award ID | 2511507 |
| Awardee | Rochester Institute of Tech |
| City | ROCHESTER |
| State | NY |
| Amount obligated | $394,869 |
| Principal investigator | Jeyhan Kartaltepe |
| Program | OFFICE OF MULTIDISCIPLINARY AC, EXTRAGALACTIC ASTRON & COSMOLO |
| Start date | 10/01/2025 |
| Abstract | Spectroscopic observations of galaxies contain critical information about their physical properties, and modern large spectroscopic surveys of galaxies are producing a plethora of data. Given the size of these datasets, traditional data analysis methods are prohibitively time consuming. The Principal Investigator (PI) will develop an artificial intelligence (AI) model called Spectroscopy Pre-trained Transformer (SpecPT) that will make use of recent advances in machine learning (ML) architectures |
| Source | NSF Awards |
$799/mo
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