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

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.

Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations, with many others, JAMA.

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.

Diagnosing Data Analytic Problems in the Classroom with Athena Chen, Eric Bridgeford, Jeff Leek, and Stephanie Hicks, Journal of Statistics and Data Science Education.

Design Principles for Data Analysis with Lucy D’Agostino McGowan and Stephanie Hicks, Journal of Computational and Graphical Statistics.

Students and Postdocs

Name Degree Current Position
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)

Made using the postcards package

Roger D. Peng


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

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.

Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations, with many others, JAMA.

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.

Diagnosing Data Analytic Problems in the Classroom with Athena Chen, Eric Bridgeford, Jeff Leek, and Stephanie Hicks, Journal of Statistics and Data Science Education.

Design Principles for Data Analysis with Lucy D’Agostino McGowan and Stephanie Hicks, Journal of Computational and Graphical Statistics.

Students and Postdocs

Name Degree Current Position
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)

Made using the postcards package