For combining machine learning with astronomy, high school senior Matteo Paz won $250,000 in the Regeneron Science Talent Search, reports Smithsonian magazine:
The young scientist’s tool processed 200 billion data entries from NASA’s now-retired Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) telescope. His model revealed 1.5 million previously unknown potential celestial bodies…. [H]e worked on an A.I. model that sorted through the raw data in search of tiny changes in infrared radiation, which could indicate the presence of variable objects.
Working with a mentor at the Planet Finder Academy at Caltech, Paz eventually flagged 1.5 million potential new objects, accoridng to the article, including supernovas and black holes.
And that mentor says other Caltech researchers are using Paz’s catalog of potential variable objects to study binary star systems.
Thanks to long-time Slashdot reader schwit1 for sharing the article.
