
Pasadena teen uses AI to sift 200 billion infrared observations, spotting 1.5 million candidates
An 18-year-old Pasadena high school senior, Matteo Paz, built a neural-network–assisted pipeline to comb through nearly 200 billion raw infrared detections from NASA's NEOWISE survey, sorting by variability to flag about 1.5 million potential new objects. Described in The Astronomical Journal and aided by Caltech/IPAC mentorship, the method turns a data firehose into manageable leads rather than confirmed discoveries. The catalog will undergo follow-up observations to confirm which candidates are real, with Paz’s win in the 2025 Regeneron Science Talent Search marking a starting line for applying the approach to future time-domain surveys.






