In a story that sounds like it came straight from a science fiction novel, 18-year-old Matteo Paz has stunned the astronomy world by discovering over 1.5 million previously unknown space objects — using artificial intelligence. With mentorship from Caltech and access to data from NASA’s NEOWISE mission, Matteo created a machine learning algorithm and compiled a groundbreaking database called VarWISE.
This discovery doesn’t just break records — it’s changing the way astronomers explore the cosmos and analyze deep space data.
From High School Student to Space Discoverer
Matteo Paz, a high school student with a passion for astrophysics and AI, began exploring public astronomical datasets during the COVID-19 pandemic. Guided by mentors at Caltech and inspired by NASA’s open data policies, Matteo taught himself how to apply machine learning techniques to mine through massive datasets — particularly the NEOWISE archive.
His AI algorithm scanned thousands of sky observations, identifying subtle light curve variations and patterns missed by traditional analysis. The result? Over 1.5 million new celestial objects, many of which may be variable stars, brown dwarfs, distant galaxies, and other exotic cosmic entities.
Introducing VarWISE: A New Cosmic Catalog
Matteo named his discovery the VarWISE catalog — short for “Variable objects discovered in WISE data.” The catalog not only expands our understanding of the universe’s structure but also serves as a critical resource for future missions and researchers.
Key highlights of the catalog include:
- Identification of 1.5 million unique space objects
- Classification of variability types and potential transients
- Cross-referencing with known objects for deeper astrophysical insight
The catalog is now publicly available and already being used by astronomers worldwide to study stellar evolution and galactic mapping.
Source: Caltech News, April 2025
NASA’s NEOWISE Data: A Treasure Trove
NEOWISE, NASA’s Near-Earth Object Wide-field Infrared Survey Explorer, has been scanning the sky in infrared since 2013. With over 15 million images and trillions of data points, it represents one of the richest astronomical archives in existence.
Matteo’s breakthrough demonstrates the power of open data and AI. By training a neural network to detect photometric anomalies, he uncovered countless objects hiding in plain sight — validating the potential of citizen science and youth-driven research.
Why This Matters
This discovery is significant not only for astronomy but also for the future of science itself:
- Shows how young minds and AI can solve complex data challenges
- Democratizes access to space research through open-source tools
- May assist in the early identification of exoplanets and transient phenomena
Caltech scientists have called Matteo’s work “on par with graduate-level research” — and his approach is now being replicated in other observatories around the world.
What’s Next for Matteo Paz?
Following the VarWISE release, Matteo has received offers from research labs and universities around the globe. He’s expected to continue his studies in astrophysics and machine learning — possibly at MIT or Caltech — and hopes to apply his skills to upcoming space telescopes like the Roman Space Telescope and ESA’s Euclid mission.
He’s also collaborating with astronomers to identify whether some of the discovered objects could be fast-moving near-Earth objects or signals from early galaxy formation.
Conclusion
At just 18 years old, Matteo Paz has already made history — and redefined what’s possible when curiosity, technology, and opportunity come together. His VarWISE catalog stands as a beacon of what young scientists can achieve with access to data, mentorship, and AI.
In an age of machine learning and massive space datasets, Matteo proves that the next great astronomer might not be in a lab — they might be coding from their bedroom.