She reached out to Danielle Bassett, a professor of physics and astronomy at University of Pennsylvania, and asked to work in her lab. Bassett invited her to be part of a project working with a group of undergraduate and graduate students to determine why certain groups of stars form recognizable patterns. David and her co-researchers wanted to know if there was a universal way that human learning occurs when it comes to collecting and organizing this information.
To find out, the team created a computer model based on the distance the eye tends to move between objects. They included two details of the night sky as seen from Earth: the distance between stars and the brightness of various stars. Using this technique, they identified constellations similar to the 88 modern constellations recognized by the International Astronomical Union, explaining how they came to be identified and named by humans.
David, who is starting at Yale University this fall, says the technique is part of a new field of applying human learning properties to naturally occurring data sets. She believes this has implications for optimizing learning and building artificial intelligence.
She and her team are currently working on a paper about their research project.
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Sophia David (far right) worked on a team in a university lab before graduating in spring 2021.
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