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*"The R-Files" is an occasional series from Revolution Analytics, where we profile prominent members of the R Community.*

Jeroen Ooms is a statistical consultant and R enthusiast currently pursuing a Ph.D. in Statistics from UCLA. Jeroen earned a B.S. in Psychology from Utrecht University in the Netherlands in 2007. It was during that time that he made his first serious foray into the world of data science, taking several statistics courses as an undergraduate. He ultimately decided to pursue a degree in that field, earning a Master's Cum Laude in Statistics and Methodology in 2009, also from Utrecht University.

It was during his Master's studies that Jeroen first started working with R. "Prior to learning R, I had done most of my programming work with Java," he says. "R is a very different environment and I was a bit skeptical at first. Initially, R looked to me like an advanced calculator that lacked important features found in most programming languages, like object oriented programming and direct memory reference. Eventually, though, I came to recognize R's simplicity as one of its greatest strengths: it is easily picked up by students, professionals and researchers and is supported by a lively community of developers and fellow users. Furthermore, R is unique in that it is both suitable as a development platform and a production platform for innovatory methods. After seeing how R is being used in a diverse range of fields and applications, I started to really appreciate the software."

After completing his M.S. at Utrecht, Jeroen looked to diversify his academic background. To that end, he spent six months as a visiting scholar at the UCLA Statistics Department from 2009-2010, studying under the renowned Jan de Leeuw. R has become the primary statistical software package used at UCLA, and plays an important role in many courses and research projects. Jeroen's work at UCLA focused primarily on developing R-based web applications for statistical education. During this time, Jeroen was accepted into the Ph.D. program at the UCLA Department of Statistics, which he began in September 2010.

Outside the classroom, Jeroen has contributed to R by developing a number of R web interfaces for popular CRAN packages, including ggplot2 for graphical exploratory analysis, lme4 for online random effects modeling, stockplot for stock predictions and irttool.com, an R web application for online IRT analysis. His web interfaces are being used in many applications, from charts tracking gender development through puberty to demographic studies.

Looking towards the future, Jeroen plans to continue developing in and contributing to the R environment as he pursues his Ph.D. from UCLA. “R is an open platform that everybody can use and contribute to,” he says. “The lifecycle of going from a good idea to production is extremely short, and greatly stimulates innovation. Once you publish your code in CRAN, others can immediately start using it or further develop it. Using R is unlike any other statistical software package: one automatically becomes part of an enthusiastic community that encourages you to share ideas, contribute code, and keep learning every day. It is science at its best”

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