As the oldest brother to 10 siblings, I've had plenty of opportunities to pass on what I've learned. I've particularly come to enjoy sharing the lessons of craft and that has attracted me to teaching the programming and analytical skills for doing computational social science. All good social science requires craft, but the relative newness of computational approaches means the craft is only just now making its way into curricula. At both the University of Michigan and Northwestern, I've developed teaching materials for instilling craft both inside and outside the classroom.

In the summer of 2018 I'll be leading an intensive two week course in computational social science at Northwestern University. It is targeted at graduate students in the social sciences and will aim to break down the mental hurdle that is a far bigger impediment to starting computational work than the practical skills of programming. I'll post more information about the course in the spring quarter.

In fall 2013 I taught my own course at the University of Michigan called Social Dynamics. This small seminar style class used mathematical and computational models to explore the types of feedback that make social dynamics an important area of research. For the course I developed a toolkit to introduce students to big data collection and analysis. This package was turned into a more general toolkit through a generous grant from the University of Michigan's Third Century Initiative. You can find the package here.

I also helped teach graduate students and faculty about how to use Python and related packages in their computational research during the University of Michigan's Advanced Research Computing's Data Analysis with Python workshop

I have completed the Center for Research on Learning and Teaching's teaching certificate and have TA'd (GSI'd in Michigan lingo) for Sociology 102 (Children and Childhood) with Karin Martin, Sociology 102 (Sports and Society) with Michael Ybarra, and Sociology 100 (Intro) with Robert Jansen.