Matteo Paz and his mentor used advanced artificial intelligence to process a vast amount of information that would have been impossible to decipher otherwise in NASA’s archives.
Matteo Paz was a young primary school student who became passionate about science and astronomy through lectures at Caltech (California Institute of Technology).
Years later, as an exceptionally keen high school student with a love for the mysterious and artificial intelligence at his side, he participated in the Planet Finder Academy programme to delve deeper into astronomy and related computer sciences.
It was his mentor, Davy Kirkpatrick, an experienced astronomer, who gave him access to the NEOWISE infrared telescope, which has reliably scanned the sky for asteroids for over a decade and also amassed a colossal amount of data on other objects.
The telescope recorded such an enormous amount of information, billions of entries, that it seemed practically impossible to decipher.
Thanks to the student’s programming courses, computer theory, and even advanced university-level mathematics, he realised that these data, when organised, were perfect for artificial intelligence.
Within six weeks, he created his own machine learning algorithm to train the AI to search for still unknown information about space.
The result: 1.5 million pieces of information about the unexplored Universe.