Researcher uses machine learning to classify stellar objects from TESS data

A game of chess has 20 possible opening moves. Imagine being asked to start a game with tens of millions of openings instead. That was the task assigned to Adam Friedman, a 2020 summer intern at NASA's Goddard Space Flight Center in Greenbelt, Maryland. A chess champion in high school, Friedman analyzed his opponent--a deluge of data on the brightness changes of over 70 million stars.