From Video Game Developer to Data Science Specialist

Kelly Peterson

Senior Data Architect, University of Utah School of Medicine

Program grad Kelly Peterson is currently a senior data architect at the University of Utah School of Medicine and a research associate in the Department of Veterans Affairs. In this interview, he talks about how the degree vastly expanded his career options. “The fact that I have this degree has opened many doors for me that a typical bachelor's in computer science could not,” he said.

What is your educational and professional background?

I received my B.S. in computer science from the University of Utah and began a career as a video game software developer. I worked at several video game studios, including Microsoft, Take-Two Interactive and Disney. It was something I enjoyed but never saw as my ultimate career path.

Why did you decide to pursue a master's degree in computational linguistics?

I have always had a passion for language that was just as strong as my interest in computers. I studied French literature for some time at the University of Utah and considered getting my undergraduate degree in linguistics instead of computer science. I finally decided to work on a master's degree in computational linguistics.

Why did you choose the UW Master of Science in Computational Linguistics?

One of the main factors was the focus and experience of the faculty. I was looking for expertise in several areas of natural language processing. I had multiple programs I could have enrolled in, but the faculty at the UW covered all the requirements I was looking for. The ability to work remotely was also a huge bonus, since it meant I was able to remain in my hometown of Salt Lake City.

What was the online learning experience like?

The online learning experience worked surprisingly well. I was able to communicate with professors and classmates using text and speech capabilities during lectures to ask questions and share ideas. I performed the majority of my coursework in Salt Lake City, although I did visit campus every two months or so to spend a week working on individual or group projects in person. A seminar I took worked extremely well in spite of the fact that a couple of us [students] were remote. The distance was not an issue for us at all. I was able to have helpful and meaningful discussions with classmates, which seriously improved the direction and quality of my own research. The interactions with and feedback from the professors were also very high quality.

Can you describe a meaningful project that you worked on in the program?

I attended Dr. Fei Xia's seminar on using methods of natural language processing in social media. Some interesting results were found during the seminar, which fit neatly into a paper. Dr. Xia recommended that I and my colleague Matt Hohensee submit the paper. It was accepted in the Language in Social Media workshop at the Association for Computational Linguistics conference and was well received.

Do you feel this program helped you enter the field of computational linguistics?

I've found that having a master's-level degree in a field like computational linguistics was essential in my job search. The faculty at the UW is very well respected, so having a master's degree from this department has been very well received. The fact that I have this degree has opened many doors for me that a typical B.S. in computer science could not.

Can you tell us about your current job?

I currently work on a number of exciting projects in Veterans Affairs on a team called BASIC, which stands for Biosurveillance, Antimicrobial Stewardship and Infection Control. I am involved in a project related to the early identification of potential infectious outbreaks and another one on helping hospitals better understand their antibiotic-prescribing patterns and their impact on veterans’ health. It’s an exciting and challenging role where I'm able to make an impact in both operations and research.

Do you feel your degree allowed you to land this position?

The program was a huge help. When I started my master’s in computational linguistics, I never realized how many of the skills I would develop would be applicable to non-textual data. For instance, In my current role, the skills I gained in machine learning allow me to work on clinical predictive models that are sometimes similar to text data but often very different. This degree and the research I performed in the course of it were absolutely critical in helping me to be in the position I am today.

Does what you learned in the program help you in your daily work?

My experience in the UW computational linguistics program definitely helps me in day-to-day work. This role in particular has forced me to stretch myself and return to NLP tasks and methods that I haven’t used much since my classwork. Luckily I still remember the principles. I am trusted as an expert in the field of text processing because no one else on my current team has that specific training. The fundamentals of feature extraction, feature selection and validation of machine learning models are part of what I do every day. They are the foundation of how I attack any new problem.