I am a fellow with a few broad interests.
Data visualization is my primary interest. I focus mainly on the interactive web-based variety of visualization. In some cases, it is in support of a visual analytics workflow, which includes an exploratory, ad-hoc browsing of information. Other tools focus on an explanatory goal of communicating information, understanding, and insight to a wider audience. These tools are sometimes less flexible while giving a sharper, more easily understood (at a glance) picture of the data.
Though I wish I were better versed in these topics, creating modern web applications isn’t possible without at least some effort to make the tool useful. In the best of all designs, the tool is more than useful. It is intuitive, familiar, comfortable, and possibly beautiful. Scientific applications are (often) judged solely by their utility. It is clear, though, that the applications which strive for more are rewarded with more users and possibly a supportive community.
How is that different from saying machine learning? In practical terms of the algorithms + software that are used to infer associations, clusters, predictive models, etc, I don’t think there’s a useful argument about the difference. To my mind, the distinction is that I am interested in the underlying statistical nature of the methodologies. How do they behave in the presence of bias and variance? How do they relate to other methods? What type of datasets do they best serve?
My wife, Jen, and I share our home with our young son, Eamon. There’s our cat, Heidi, too. We spend a lot of time together having fun in one way or another. Often it is trips to the zoo and the playground. Lately, the Museum of Flight has become a favorite.
I have been playing ultimate frisbee since 2000. After playing on my college team for a few years, I came to Seattle where the community is amazing. I have played on two teams for a majority of the 13 years. Space Invaders is a great crowd of friends (more like family). Outside of playing, I coached middle school for a few seasons. I co-coordinate an adult hat league, called Verns, with my great friend Steve. Verns is set up to bring friendly, experienced players together with many inexperienced adults to learn the skills, rules, and spirit of ultimate in a supportive, educational environment.