VarWISE — the First Complete Infrared Variability Survey — 1.9M Variables Classified into 10 Classes
Matteo found a way to convert a decade’s worth of full-sky data into a catalog of hidden rare stars and galaxies.
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Matteo Paz, 18, of Pasadena, surveyed nearly 200 terabytes of astronomical data in search of undiscovered brightness-variable objects for his Regeneron Science Talent Search space science project. After over a decade of scanning the sky, NASA’s WISE space telescope collected all-sky infrared data, creating a treasure trove of nearly 200 billion lines of data for time-based astronomical research.
In his project, Matteo developed waveform-based machine learning methods to sort the entire catalog and efficiently detect and characterize potential variables within the telescope’s data, including a machine-learning algorithm dubbed VARnet. He produced a complete census of 1.9 million infrared variable objects, 1.5 million of which are new discoveries, including supermassive black holes, newborn stars and supernovae. His project was carried out as a staff researcher under NASA funding.
Matteo, the child of Amy and Pedro Paz, attends Pasadena High School. He is president and founder of the research club, where he mentors others in science contests. Matteo also served on his district’s first unified student council and as a student assembly representative for the school board.
Beyond the Project
Matteo founded and runs a program called Money Matters — Financial Education for the Youth. They visit middle schools and teach about financial basics and money literacy.
FUN FACTS: Matteo owns a concert promotion business called Elbows, which lets him deeply connect with the Los Angeles music scene and support the music he loves.
