The astronomy world was recently shaken by a discovery from an unexpected source: a teenager still in high school. Matteo Paz, a student from Pasadena, utilized archival data from NASA’s retired NEOWISE mission to bring 1.5 million invisible cosmic objects into the light.
During a stint at Caltech’s Planet Finder Academy, and mentored by astrophysicist Davy Kirkpatrick, Paz took a novel approach to data analysis. He built a unique machine learning model capable of sifting through a staggering 200 billion infrared records. In a span of only six weeks, his AI detected subtle patterns that human analysts had missed, identifying everything from distant quasars to exploding supernovas.
Paz’s findings were so robust that they earned him a spot in the prestigious The Astronomical Journal and a position as a research assistant at Caltech. His work does more than just populate star maps; it provides specific coordinates for the James Webb Space Telescope to investigate further. This breakthrough highlights a growing trend where fresh perspectives and AI tools allow young researchers to make historic scientific impacts from the classroom.