Each quarter, the Center for Health and Environment: Education and Research spotlights a faculty member active in research in health and the environment. This installment features Roger Peng, Ph.D., a professor of statistics and data sciences in the College of Natural Sciences at The University of Texas at Austin.
About Peng & His Work
Prior to joining UT, Peng was professor of biostatistics at the Johns Hopkins Bloomberg School of Public Health and the co-director of the Johns Hopkins Data Science Lab. Upon concluding that he didn’t have much of a future as a classical violinist, Peng pursued a Ph.D. in statistics at the University of California, Los Angeles. Afterward, he was a postdoctoral fellow at Johns Hopkins University, where he studied the various effects of air pollution on human health.
Peng has developed statistical methods for assessing the health impacts of outdoor air pollution using large national databases. He applied these methods to administrative data from Medicare, Medicaid and the National Center for Health Statistics to develop strong evidence that outdoor air pollution, even at today’s low levels, is associated with increased cardiovascular and respiratory diseases. This evidence was subsequently used to inform the Environmental Protection Agency’s National Ambient Air Quality Standards for particulate matter and ozone.
Peng has also developed new statistical approaches to studying the health effects of indoor air pollution. In a study conducted in Baltimore, Maryland, Peng’s methods showed that reducing indoor particulate matter could have a significant positive impact on asthma symptoms in children. Finally, Peng has also made important contributions to the study of climate change and health. His work has demonstrated that extreme climate-related weather events, such as heat waves, wildfires and tropical storms, are associated with significant morbidity and mortality, often much higher than is directly connected with the extreme events. For his work in environmental biostatistics, Peng received the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health.
Peng is also interested in data science theory and pedagogy. His current work focuses on the theory and methods for building successful data analyses. With collaborators from Wake Forest University and Johns Hopkins University, he published a framework for specifying design principles for building data analyses. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics.
Peng is also the co-creator of the Simply Statistics blog, where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker and The Effort Report podcast with Elizabeth Matsui.
What would be the most surprising scientific discovery imaginable?
Peng: “Life on Mars would be surprising. But life on Europa would be cool.”