# Pasadena High School Student's ML Algorithm Discovers 1.5M Variables in NASA Data

> A high school student in Pasadena built a machine learning algorithm that combed through NASA's NEOWISE telescope data and turned up more than 1.5 million previously unknown variable light sources. These are objects whose brightness changes over time, and finding them at this scale is a meaningful contribution to astronomy. The approach leaned on established signal-processing techniques, using Fourier transforms and wavelet analysis to detect periodic patterns buried in enormous streams of observations. What makes it notable is not a brand new method so much as the scale and the source: a student applying accessible tools to a public dataset and surfacing results professionals had not yet catalogued. It is a small story with an outsized point. As datasets balloon and analysis tools become widely available, discovery is no longer confined to large institutions. The same pattern-finding that powers commercial AI can be pointed at the sky by anyone with curiosity and the right code.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: AI Business Weekly · Published Wednesday, September 2, 2026_

## Wortins' read

A high school student in Pasadena built a machine learning algorithm that combed through NASA's NEOWISE telescope data and turned up more than 1.5 million previously unknown variable light sources. These are objects whose brightness changes over time, and finding them at this scale is a meaningful contribution to astronomy. The approach leaned on established signal-processing techniques, using Fourier transforms and wavelet analysis to detect periodic patterns buried in enormous streams of observations. What makes it notable is not a brand new method so much as the scale and the source: a student applying accessible tools to a public dataset and surfacing results professionals had not yet catalogued. It is a small story with an outsized point. As datasets balloon and analysis tools become widely available, discovery is no longer confined to large institutions. The same pattern-finding that powers commercial AI can be pointed at the sky by anyone with curiosity and the right code.

## Source

[Read the full story at AI Business Weekly](https://aibusinessweekly.net/p/chatgpt-ads-nvidia-heart-disease-ai-news-september-1-2026/)

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_Curated and written by [Wortins](https://www.wortins.com) — The daily AI briefing. Every story links to its original source; the "Wortins read" on each is our own original analysis. [About Wortins & our editorial approach](https://www.wortins.com/about)._