COMPUTATIONAL SOCIAL SCIENCE

Meet a Student: Kevin Comer

Kevin Comer is a Ph.D. candidate in the Department of Computational Social Science. His research is focused on modeling the drivers and effects of adverse selection, or non-participation, in markets. His dissertation topic is the simulation of this phenomenon, using agent-based models, in the context of the individual health insurance market

What is your background?

 I have a B.S. in Systems Engineering and a B.A. in Economics from the University of Virginia from 2007, and an M.S. in Military Operations Research from George Mason University from 2010.

Why did you choose CSS at GMU?

Computational social science allows me to investigate the issues and phenomena we see in the modern, natural world, full of complexity and interconnections. My background is heavily based in computational methods and modeling, but much of it was geared towards either engineered, designed systems, or abstracted models to the point of absurdity. Computational social science takes the world for what it is, rather than how they "should" be. The CSS Department at George Mason is quickly becoming a world leader in this interdisciplinary field. Researchers from Europe, Asia and the Americas continue to speak highly of the work done by our department, and I'm glad to be a part of that.

What courses have you done and what have you enjoyed about them?
 

The first class I took was Robert Axtell's CSS 610 course, which changed my dislike for the highly stylized and abstracted mathematics in mainstream economics used today, into a love of the rigorous, pertinent, and applicable methods of understanding economic complexity in the modern world. I have also enjoyed Claudio Cioffi's classes, both CSS 620 and CSS 625. The Origins of Social Complexity (CSS 620) helped me to understand the formal logic that sociologists use for understanding social development, and Complexity Theory in the Social Sciences (CSS 625) gave me the quantitative, computational tools to understand and test for complexity. 

What is your research area/PhD topic?

My PhD dissertation is on adverse selection, or non-participation, in markets, specifically on the individual health insurance market. However, my research interests are much more broad and interdisciplinary. I have written papers on a wide variety of topics, including emergent social complexity in Ireland, network effects in tax evasion modeling, relationship networks across European royalty, the emergence of social inventions in renaissance Florence, and power laws in the public debt.