Carl Kingsford, PhD, is a professor in the Computational Biology Department within the School of Computer Science at Carnegie Mellon University. He’s also the Chief Science Officer at the Center for Machine Learning and Health.
Where did your career begin? What did you do? What were the most important lessons you learned there?
After receiving my PhD, I started as a Postdoc at the University of Maryland, College Park in Steven Salzberg’s group. My PhD work had been on biological network analysis and protein structure prediction. In Steven’s group, I learned a lot about genomics and also a lot about how to pick good research problems.
You’re originally from upstate New York, what brought you to Pittsburgh?
I moved to Pittsburgh in 2012 from Silver Spring, MD. I had been an assistant professor of Computer Science at the University of Maryland, College Park. I was attracted to Carnegie Mellon by its relatively new Computational Biology Department (then called the Lane Center for Computational Biology) within the School of Computer Science. And of course I was attracted by Pittsburgh, which is a great place to live.
What led you to the Pittsburgh Health Data Alliance?
We had been working on a number of computational methods for analyzing genomics data in my research group. I wanted to apply our research on genomics methods more directly to questions about health and to help translate our work and other’s work into wider use and more clinical settings.
What trends are you most excited about today in data and healthcare? Why?
Certainly the increased availability of DNA and RNA sequencing and its quickly lowering cost is a very exciting development in healthcare. With large collections of sequencing experiments that are now becoming available, I am hopeful that new, accurate predictive models can be trained that will help doctors make better, and more personalized, treatment choices.
What’s a fun fact that most people don’t know about you?
I completed the Pittsburgh Marathon in 2013.