Meet Emily Silgard, Fred Hutchinson Cancer Research Center‘s resident artificial intelligence expert. According to a company spokesperson, Silgard applies her data/technical expertise on scientific research projects, including a recent study utilizing natural language processing to better track lung cancer patients.

Here, Seattle-based Silgard answers some questions about her work.

What do you do? I lead a data science team at Fred Hutchinson Cancer Research Center. Our team’s primary focus is building tools and services to help support data intensive research and Fred Hutch’s mission of eliminating cancer and related disease. We wrangle data and develop machine learning and software applications to get the right information to our scientists.

How did you get started in this field? I started out as an undergrad studying linguistics. I loved every minute of it, but it wasn’t super applicable. Then I studied computational linguistics at the University of Washington, which is essentially about getting computers to process human language. After learning how to code and how to approach machine learning problems, I did an internship in the biomedical domain and knew I’d found that application I was looking for.

What’s a typical day like? Usually at least a couple of meetings: with researchers to learn more about their studies and their obstacles, and with my team to figure out how we can help solve those issues.

I try to go to the scientific presentations on campus whenever I can to learn more about all the cool work people are doing.

I code; I build —and sometimes break — programs; I solve puzzles. And I read and research. Trying to support work at the intersection of two rapidly evolving fields — computer science and biomedical science — really requires keeping up to date so we can plan for how we can best support the science tomorrow.


What’s the best part of the job? My team. I get to show up and go to work every day with these really smart, funny people who work hard to make an impact. And I love being exposed to the science. I’m continually amazed by the work being done at Fred Hutch.

What surprises people about what you do? The machine learning algorithms themselves are always the smallest piece of the puzzle. We spend so much more time learning as much as possible about the people, the data and the process, so that we can find solutions with the biggest possible impact.

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