In a remarkable blend of youthful ingenuity and cutting-edge technology, teenager Matteo Paz has made headlines across the scientific community after discovering 1.5 million previously hidden stars using artificial intelligence (AI). This extraordinary achievement, which involved analyzing data from NASA’s NEOWISE space telescope mission, has earned high praise from NASA Administrator Jared Isaacman and showcases the immense potential of AI in advancing our understanding of the cosmos.
The Discovery: A Teen’s Quest to Map the Invisible
Matteo Paz, a high school student from Pasadena, California, made this groundbreaking discovery while participating in Caltech’s Summer Research Connection outreach program. Working with astronomers at the California Institute of Technology, Paz developed an AI model to analyze archived data from NASA’s NEOWISE mission, a task that would have been virtually impossible to accomplish manually.
The NEOWISE archive contains more than 200 billion data points collected over a decade, making traditional analysis methods inadequate for uncovering hidden celestial objects. As Paz himself noted, “I mapped the invisible,” referring to his ability to detect objects that flickered, pulsed, or dimmed—behaviors often linked to quasars, eclipsing binary stars, or supernovae but previously overlooked in the vast dataset.
NASA’s NEOWISE Mission: A Treasure Trove of Astronomical Data
To fully appreciate the significance of Paz’s discovery, it’s important to understand the NEOWISE mission that provided the data for his research. Originally launched as the Wide-field Infrared Survey Explorer (WISE) in December 2009, the spacecraft was later reactivated in 2013 under the Near-Earth Object Observations Program as NEOWISE.
The entire sky as seen by NASA’s NEOWISE mission in infrared light. Credit: NASA/JPL-Caltech
NASA’s NEOWISE mission was primarily designed to detect and characterize near-Earth objects such as asteroids and comets. The spacecraft mapped the entire sky multiple times in infrared wavelengths, creating a rich dataset that has proven invaluable for various astronomical studies. During its primary mission, NEOWISE detected more than 158,000 minor planets, 34,000 of which had never been discovered previously.
The mission’s focus on infrared observations was particularly important because many celestial objects, including brown dwarfs and distant galaxies, are more easily detected in infrared light than in visible light. This makes the NEOWISE dataset especially valuable for discovering objects that might be missed by traditional optical telescopes.
The Technology Behind the Discovery: AI, Fourier, and Wavelet Analysis
Paz’s achievement was made possible through a combination of machine learning techniques and sophisticated mathematical analysis. He built an AI model using Fourier and wavelet analysis, mathematical techniques ideal for studying evolving signals that change over time.
Fourier analysis breaks down complex signals into simpler sine and cosine waves, making it easier to identify periodic patterns in data. Wavelet analysis, on the other hand, is particularly good at detecting transient signals—short-lived changes that might be missed by other methods. By combining these techniques in his AI algorithm, Paz was able to identify subtle variations in the infrared spectrum that had been previously invisible due to NEOWISE’s temporal sampling limitations.
The computational challenge was immense. Processing the entire NEOWISE dataset manually would have taken centuries, if not longer. However, Paz’s AI model was able to analyze the complete dataset in just six weeks, surfacing 1.5 million candidates for further investigation. This demonstrates the transformative potential of AI in astronomical research, where datasets are growing exponentially larger and more complex.
Recognition from the Top: NASA Administrator’s Praise
Paz’s work caught the attention of NASA Administrator Jared Isaacman, who praised the young researcher’s innovative approach. Isaacman, who became NASA’s 15th administrator in December 2025, recognized that Paz’s discovery not only impressed NASA’s researchers but also demonstrated how fresh perspectives and advanced technology are revolutionizing astronomical discovery.
The recognition went beyond words of praise. As a testament to the significance of Paz’s work, NASA offered him both a job opportunity and a fighter jet ride—an extraordinary honor for a high school student. This recognition underscores NASA’s commitment to encouraging young talent and embracing innovative approaches to space exploration and research.
Broader Implications: AI’s Role in Space Exploration
Paz’s discovery is part of a larger trend in astronomy and space exploration: the increasing use of AI to analyze vast datasets and uncover previously hidden phenomena. As space missions become more sophisticated and generate ever-increasing amounts of data, traditional analysis methods are becoming inadequate.
This shift is evident in several recent astronomical discoveries:
- The use of machine learning to identify exoplanets in Kepler mission data
- Galaxy classification projects like Galaxy Zoo that harness citizen science and AI
- Automated detection of supernovae in large astronomical surveys
- AI-assisted analysis of gravitational wave data from LIGO
Paz’s work builds on these advances while demonstrating new applications of AI in analyzing infrared astronomical data. His success suggests that similar approaches could be applied to other large datasets, potentially uncovering millions of additional celestial objects that have been hiding in plain sight.
Impact on Astronomical Research
The discovery of 1.5 million previously hidden stars has significant implications for our understanding of the cosmos. These objects represent dynamic, energetic phenomena that could rewrite parts of our understanding of how the universe evolves. The fact that such a large number of objects were found in existing data, rather than through new observations, highlights the potential for re-analyzing archival data with new techniques.
Moreover, Paz’s peer-reviewed paper, published in The Astronomical Journal as a single-author work, demonstrates that significant scientific contributions can come from unexpected sources. At just 18 years old, Paz has not only made a substantial discovery but has also advanced the scientific potential of the NEOWISE mission data.
The recognition of his work extends beyond NASA. Paz was awarded $250,000 in the Regeneron Science Talent Search, a prestigious competition that recognizes outstanding research by high school students. This award further validates the significance of his contribution to astronomical research.
Looking to the Future
As we look toward the future of space exploration, Paz’s work serves as a compelling example of how AI can augment human intelligence in scientific research. With upcoming missions like the Vera C. Rubin Observatory expected to generate unprecedented amounts of data—approximately 20 terabytes per night—AI analysis techniques will become increasingly essential.
Paz’s success also highlights the importance of educational outreach programs that connect young people with real scientific research. His participation in Caltech’s Summer Research Connection program provided him with the mentorship and resources needed to make this discovery. Such programs demonstrate that with proper support and access to data, young researchers can make significant contributions to scientific knowledge.
The story of Matteo Paz and his 1.5 million hidden stars represents a convergence of several important trends: the democratization of data access, the power of AI in scientific discovery, and the potential for young minds to contribute meaningfully to our understanding of the universe. As AI continues to evolve and datasets grow larger, we can expect more discoveries like this one, potentially uncovering millions of additional celestial objects that have been waiting patiently in archival data.
Whether Paz continues his research career or pursues other interests, his work has already left an indelible mark on astronomy. His innovative approach to analyzing the NEOWISE dataset not only earned him recognition from NASA’s top official but also opened new possibilities for how we explore and understand the cosmos.
Sources
NASA NEOWISE Mission – Official NASA mission page providing details about the NEOWISE spacecraft and its discoveries.
NEOWISE Mission Summary at JPL – Jet Propulsion Laboratory’s overview of the NEOWISE mission, including key findings and technical details.
The NEOWISE Project – Caltech’s official website for the NEOWISE project, managed by the Infrared Processing and Analysis Center.
A Sub-Millisecond Fourier and Wavelet Based Model to Extract Variable Candidates from the NEOWISE Single-Exposure Database – Technical paper describing the AI methodology used in Paz’s research.
California Institute of Technology – Caltech’s official website, where Paz conducted his research.
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