Mathematics graduate student aims high with NASA

In March, as the world shut down due to the COVID-19 pandemic, students and potential employers were left changing plans, and many

Photo of a Zoom call.
Michael Moy pictured in the top left on a call with fellow NASA interns and staff.

internships and experiences were canceled.

If anyone could traverse the technological spacetime and give students the opportunity to learn and grow in their fields of study, it would be NASA. As a result, Colorado State University mathematics graduate student Michael Moy was one of NASA’s virtual interns this summer.

Moy interned from his home in Fort Collins with researchers at NASA’s Glenn Research Center in Cleveland, Ohio, through the SCaN Intern Project, designed to give students a paid 10-week internship in the field of space communication and navigation. Although the internship might have looked different than previous years, Moy said it was “overall a really positive experience.” Even though he worked from home, constantly meeting with the other interns “made for a really good sense of community.”

Hands-on experience

The internship at the Glenn Research Center gave Moy solid hands-on experience. He spent the summer applying math to communication and navigation in space flights. He applied this work to both machine learning and pathfinding algorithms used in networking – how a

Photo of Michael Moy in a Zoom Call
Michael Moy on an online call for his internship with NASA.

machine processes communication and path decisions.

Moy said that the purpose of the work was to try to expand the current capabilities in this field in a way that would specifically benefit NASA.

Moy’s team has sent their first paper, titled “Path Optimization Sheaves” to the NASA review process. They hope to publish it in arXiv, an open access online repository for papers in the technical sciences. Eventually they want to publish the paper in a formal journal. There are also tentative plans for a second paper, based on their work using topological data analysis to examine neural networks.

Through the internship, Moy became interested in topological data analysis, which is a “relatively recent area of math,” he said. He is currently considering topics for his graduate study project at CSU.

Moy said his future is a bit uncertain right now, but hopes to land an industry job soon. “I want to do math professionally in a useful and meaningful context,” he said. “It’s been helpful to be able to draw on that background as I work here.”