A little context…


While my interest is in statistical and data science, I started off majoring in psychology and philosophy as an undergraduate, and eventually obtained a Ph.D. in Experimental Psychology. During graduate school, I became interested in statistics, eventually choosing it as a concentration, and I also started consulting at that time. That turned out to be a good fit for me, and I’ve been exploring and analyzing data ever since.

Previous to my current position, I was a statistical consultant for the Center for Social Science Research at the University of Notre Dame. Before that, I was previously affiliated with the University of North Texas with the departments of Psychology as lecturer, and Data Science and Analytics as statistical consultant.


Currently I am Statistician Lead for the Advanced Research Computing consulting group, CSCAR, at the University of Michigan. I provide analytical, visualization, code, concept, and other support to the larger research community. Analytically speaking, I have a fairly wide exposure to modeling techniques, from traditional models, to their extensions dealing with clustered data, temporal, spatial and nonlinear contexts, latent variable models, machine learning techniques, Bayesian approaches, dealing with unstructured data (e.g. text analysis), and so on. I spend most of my programming time in the R world, with which I have many years of experience using it as my primary programming tool. Lately, I have spent the bulk of my non-R coding with Python and Stan. However, I have had exposure to traditional statistical packages, and some more specialized. I also have to consistently dive into web-oriented programming as necessary, e.g. markdown, css and the like, and use tools like R and Python for web-scraping. I like programming and solving problems with it, and I’m lucky enough to spend regular time simply learning new statistical and programming tricks.

What drew me to the world of statistics and keeps my interest is that it frees me to engage in whatever science I like, and provides a great many tools with which to discover more about the things we humans are most interested in. CV can be found here.

Michael Clark

Consulting for Statistics, Computing, & Analytics Research
Advanced Research Computing
University of Michigan


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