Bio
Roger D. Peng is a Professor of Statistics and Data Sciences at the University of Texas at Austin. Previously, he was Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and the Co-Director of the Johns Hopkins Data Science Lab. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health. Roger received a PhD in Statistics from the University of California, Los Angeles. His current research focuses on building analytic design theory for improving the quality of data analyses and on the development of statistical methods for addressing environmental health problems.
Recent Work
Opportunities for using artificial intelligence in air pollution and health research, with Sarah Chambliss, Journal of Allergy and Clinical Immunology.
A causal machine-learning framework for studying policy impact on air pollution: A case-study in COVID-19 lockdowns, with Claire Heffernan, Kirsten Koehler, Cody Buehler, Drew Gentner, and Abhirup Datta, American Journal of Epidemiology.
A dynamic spatial filtering approach to mitigate underestimation bias in field calibrated low-cost sensor air-pollution data with Claire Heffernan, Drew Gentner, Kirsten Koehler, and Abhirup Datta, Annals of Applied Statistics.
Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations, with many others, JAMA.
Design Principles for Data Analysis with Lucy D’Agostino McGowan and Stephanie Hicks, Journal of Computational and Graphical Statistics.
Books
R Programming for Data Science
Tidyverse Skills for Data Science in R, with Stephanie Hicks, Shannon Ellis, and Carrie Wright
The Art of Data Science, with Elizabeth Matsui.
Exploratory Data Analysis with R
Check out all my books on LeanPub
Students and Postdocs
| Name | Degree | Current Position |
|---|---|---|
| Lydia Lucchesi | Postdoctoral Fellow | |
| Sarah Coleman | Postdoctoral Fellow | |
| H. Sherry Zhang | Postdoctoral Fellow | |
| Matthew Vanaman | Postdoctoral Fellow | |
| Claire Heffernan | PhD, Biostatistics | Merck |
| Xinyu (Sindy) Du | ScM, Biostatistics | Harvard University |
| Jia Coco Liu | Postdoctoral Fellow | Meta / Facebook |
| Kayleigh Keller | Postdoctoral Fellow | Colorado State University |
| Helen Powell | Postdoctoral Fellow | University of Maryland |
| Katherine Freeland | ScM, Biostatistics | Sandia National Labs |
| Amber Hackstadt | Postdoctoral Fellow | Vanderbilt University |
| Brooke Anderson | Postdoctoral Fellow | Colorado State University |
| Jenna Krall | PhD Biostatistics | George Mason University |
| Detian Deng | ScM, Biostatistics | ByteDance |
| Jennifer Bobb | PhD, Biostatistics | Kaiser Permanente Washington Health Research Institute |
| Howard Chang | PhD, Biostatistics | Emory University |
| Renjie Chen | Visiting PhD Student | Fudan University |
| Maggie Matsui | Summer Intern | Etsy |
| Nichole Kyprianou | Summer Intern | Wake Forest University |
Education
Ph.D. in Statistics | University of California, Los Angeles (Advisor: Frederic Schoenberg)
M.S. in Statistics | University of California, Los Angeles
B.S. Applied Mathematics | Yale University (Advisor: Nicolas Hengartner)
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