How a High School Student's AI Project Discovered 1.5 Million New Objects in Space
- Christina
- Jul 14, 2025
- 5 min read
How a high school student’s machine learning project led to real-world impact and a $250,000 prize?
Table of Contents
High School Student Uses AI to Analyze NASA Telescope Data
Matteo Paz didn’t have access to a lab or telescope. What he had was curiosity, Python, and a public NASA dataset.
While most researchers were focused on tracking asteroids, Matteo trained an AI model called VARNet to detect everything else: variable stars, black holes, cosmic flickers that had gone unnoticed.
The result? His model flagged 1.9 million objects. Over 1.5 million were brand new to astronomy.
Machine Learning in Astronomy: How Matteo Did It at Age 17
He used data from NASA’s NEOWISE mission, which scanned the entire sky in infrared for more than a decade. That’s hundreds of billions of data points, enough to make most heads spin.
But Matteo didn’t get overwhelmed. He built a machine learning model that analyzed brightness fluctuations in stars over time, identifying patterns using wavelet transforms and Fourier analysis.
This wasn’t just a science fair project. His work was published in The Astronomical Journal. And he took home $250,000 at the Regeneron Science Talent Search https://www.societyforscience.org/regeneron-sts/2025-student-finalists/matteo-paz/, one of the most prestigious science competitions for high schoolers in the U.S.
The Power of Mentorship in High School STEM Projects
Behind Matteo’s success was a key figure: Dr. J. Davy Kirkpatrick, senior scientist at Caltech. When Matteo told him he wanted to publish his research, Kirkpatrick didn’t say, “Maybe later.” He said, “Let’s talk about that.”
That one line made all the difference. It’s proof that real mentorship isn’t just helpful, it’s essential.
Why AI Projects for High School Students Matter More Than Ever
If you’re a high schooler or the parent of one, here’s what Matteo’s story proves:
You don’t need a PhD to use real data. You need direction.
AI and machine learning are not college-level-only tools anymore.
High schoolers can publish. They can compete. They can get taken seriously.
The right mentor can turn a vague interest into a world-class result.
From Curiosity to Code: Star Gazer, Built by a High School Student
A few months ago, a student at BetterMind Labs took on a challenge that felt way out of reach: tracking how star brightness shifts over time. Inspired by space missions like NEOWISE, the student built Star Gazer, a tool that uses machine learning to classify variable stars based on their light curves.
He didn’t start with a background in astrophysics. But he had questions and a mentor who helped him follow them to a working prototype. His project didn’t just end with a presentation. He’s now exploring real-world datasets and refining them further for publication.
Projects like this are becoming more common, not because students are “geniuses,” but because the tools, guidance, and ambition finally line up.
Check out BetterMind Labs AI + Space Exploration projects that High School Students can build.
FAQs
Who is Matteo Paz and why is his AI project significant?
Matteo Paz is a high school researcher who developed VARNet, a machine learning model that analyzed NASA's NEOWISE data to identify variable objects in space. His research led to the discovery of more than 1.5 million previously unknown astronomical objects and earned him the $250,000 top prize at the Regeneron Science Talent Search.
Can high school students really build advanced AI projects?
Yes. With access to public datasets, open-source tools, and strong mentorship, high school students can build sophisticated AI projects in fields such as healthcare, astronomy, finance, climate science, and cybersecurity. Many students are already conducting research and developing solutions with real-world impact.
Do students need advanced math or coding experience to start AI?
Not necessarily. Many students begin with little or no experience. Learning Python, data analysis, and basic machine learning concepts step by step allows students to gradually build the skills needed for more advanced AI applications.
Why is mentorship important for AI and research projects?
Mentorship helps students identify meaningful problems, avoid common mistakes, and develop stronger technical solutions. Experienced mentors also provide guidance on research methodology, data analysis, project presentation, and publication opportunities.
Can AI projects help with college admissions?
Absolutely. Meaningful AI projects showcase initiative, intellectual curiosity, problem-solving ability, and real-world impact. Projects often become powerful topics for college essays, research competitions, scholarship applications, and interviews because they demonstrate how students apply knowledge beyond the classroom.
Final Takeaway: The Future of STEM Belongs to Students Who Start Early
Matteo Paz's story is remarkable, but the lesson isn't that he was extraordinary. The lesson is that he started. He found a problem that interested him, learned the tools he needed, worked with mentors, and stayed committed long enough to create something meaningful.
That same pattern appears again and again among successful students. The strongest college applicants, scholarship winners, and young researchers are not simply consuming knowledge. They are applying it. They build, test, iterate, and solve problems that matter.
At BetterMind Labs, we see this transformation happen every year. Students begin with curiosity and leave with projects that tackle challenges in healthcare, finance, sustainability, cybersecurity, and even astronomy. Like Matteo, they learn to work with real datasets, develop machine learning models, and create solutions that extend far beyond a classroom assignment.
The goal is not to replicate someone else's success story. It is to create your own.
Whether you're analyzing telescope data, building an AI healthcare tool, or designing a sustainability solution, the opportunity to make an impact starts much earlier than most people realize. The tools are available. The data is available. The mentorship is available.
The students who will shape the future of science and technology are not waiting until college to begin.
They're already building.
And at BetterMind Labs, we're helping them turn curiosity into research, projects into impact, and ideas into opportunities. Checkout BetterMind Labs AI ML Program designed for High School Students (8th to 12th Graders)
Relevant Keywords:
Regeneron STS 2025 Finalist – Matteo Paz https://www.societyforscience.org/regeneron-sts/2025-student-finalists/matteo-paz/
NASA NEOWISE Mission Update – April 2025 https://neowise.ipac.caltech.edu/news/neowise20250411/
Pranav Sivakumar’s Research Project – Astronomical League PDF https://www.astroleague.org/files/awards/Pranav_Sivakumar_project.pdf
Pranav Sivakumar – Wikipedia https://en.wikipedia.org/wiki/Pranav_Sivakumar
Sloan Digital Sky Survey – Educational Resources https://classic.sdss.org/education/
Fermilab High School Student Internship Programs https://internships.fnal.gov/high-school-student-programs/
BetterMind Labs – AI Projects by High School Students https://www.bettermindlabs.org/
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