High-School Student Discovers 1.5 Million Space Objects
Matteo Paz, an 18-year-old California high-school student, used a machine-learning pipeline to analyze NASA's NEOWISE archival data and identified over 1.5 million previously unidentified space objects, in work published in The Astronomical Journal in 2024 and awarded the $250,000 Regeneron Science Talent Search prize. Paz processed roughly 200 billion detection rows to detect faint variable sources, suggesting the pipeline could scale to other telescopes' archives.
Key Points
- 1Detects over 1.5 million previously unidentified space objects using NEOWISE archival data and ML
- 2Processes roughly 200 billion detection rows, enabling systematic classification of faint variable stars and transients
- 3Offers practitioners a scalable ML pipeline for mining archival telescopic datasets like Kepler or Roman
Scoring Rationale
Significant peer-reviewed discovery and reusable ML pipeline drive the score; limited broader methodological detail reduces scope slightly.
Sources
Public references used for this report.
Practice interview problems based on real data
1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
