Broadening the Scope on Statistics Careers
“My fiancé says it’s like a little kid’s dream,” says Mitchell Kinney, “I’ve always wanted to work at NASA, the NFL, and Disney World.” Kinney is a fifth-year PhD candidate in the School of Statistics and the recipient of the 2019 Doctoral Dissertation Fellowship. What started out as a childhood dream became reality when Kinney was offered a summer internship with the NASA Jet Propulsion Laboratory two summers ago.
Kinney attended the University of Iowa for his undergraduate degree, where he majored in statistics, computer science, and math. He knew he wanted to pursue a PhD but was originally thinking it would be in computer science. Kinney was driven toward a PhD in statistics because of the vast amount of job prospects that an advanced degree in statistics would offer him. As Kinney puts it, “You can do insurance, you can do science, you can do sports, really anything.”
For his dissertation, Kinney has chosen to explore applications of deep learning methods. He explains his research question: “Very vaguely, it’s about question-and-answering. More specifically, it’s exploring how to condense words into number representations so you can use classical statistical methods in order to learn the relationship between questions and answers.”Kinney’s research determines how information from a textbook, for example, could be condensed into an electronic knowledge base that is able to return the correct response when queried.
While most PhD work is done independently, Kinney enjoys engaging with other graduate students in the School of Statistics. Last year he facilitated the student seminar series, which is a weekly program that gives students the opportunity to present their research in front of other students—no faculty allowed. “This program allows other students to understand what kind of research has been done in the department and, for some, connects them with advisors,” says Kinney.
From Classroom to Lab
Kinney was drawn to a NASA internship not only because of his childhood dream but because of the nature of his work there. With an advanced degree in statistics “you can work for companies like Google, Facebook, and Amazon, but you’re pretty much getting paid to figure out how to make people click on things.” Kinney wanted to do more than that.
This past summer at NASA, Kinney worked with a team to determine exactly where a boat on Earth is positioned in global space, based on just two cameras and a geographic location. As Kinney explains, “Essentially, we were trying to autonomize driving boats because if you can map out objects in the ocean, then you can autonomously drive boats to avoid those objects.” Kinney thoroughly enjoyed working on this project because “autonomy is what will allow exploration to explode in the future. With autonomy, human costs are significantly reduced while we are still reaping the benefits.” NASA has given him the opportunity to work on exciting projects that have very valuable applications for the future.
In addition to spending two summers at NASA, Kinney also spent one winter working on a project for the 2019 NFL Big Data Bowl. He won an honorable mention for his work on classifying receiver routes and route combinations that lead to a successful play during a football game.
To the Future and Beyond
“I chose Minnesota because I wanted to go to a school where your effort determined your outcome,” says Kinney. “I see PhD students here all the time ending up at big companies like Apple or Google, or R1 [doctoral] universities,” he furthers.
Kinney has certainly taken advantage of opportunities at the University of Minnesota, as he’s become a shining star in the School of Statistics: from leading the student seminar series, to receiving the School of Statistics Director’s Award last spring, to ending his educational career as a doctoral dissertation fellow.
As Kinney wraps up his degree, he is excited about graduation and hopes to end up back at NASA’s Jet Propulsion Lab with a full-time position. And, of course, someday work for Disney.
This story was written by an undergraduate student in CLA.