Serre, ESE faculty member, becomes associate professor
|August 20, 2009|
Marc Serre, PhD, has been promoted to associate professor of environmental sciences and engineering, with tenure, in the University of North Carolina at Chapel Hill’s Gillings School of Global Public Health. The new appointment is effective Sept. 1.
Serre joined UNC’s Department of Environmental Sciences and Engineering in 2001 and was appointed assistant professor in 2002. He is director of the UNC Bayesian Maximum Entropy Laboratory for Space/Time Geostatistics in Exposure, Disease and Risk-Mapping.
Serre earned a Master of Science degree in civil and environmental engineering from the University of Iowa in 1992 and a Doctor of Philosophy in environmental modeling from UNC-Chapel Hill in 1999. While completing his doctorate, he was a computational science research fellow and, later, did postdoctoral research at UNC. He spent a year in Egypt (1999-2000) studying air quality.
Serre’s research interests range from space/time geostatistics and temporal geographic information system (GIS) atmospheric mapping of air pollutants to environmental justice. He is working on projects that apply space-time statistics to model a variety of environmental and health processes, including fecal contamination of drinking water and childhood diarrheal disease in Bangladesh and the spread of sexually transmitted infections in North Carolina.
In May 2005, Serre won the Newton Underwood Memorial Award for Excellence in Teaching, presented to environmental sciences and engineering faculty members who exhibit conscientious dedication to students and teaching.
“[Serre’s] innovative research on the combined temporal and spatial analysis of environmental and human health data provides an important tool in understanding correlations of pollutant concentrations with disease outcomes,” says Michael Aitken, PhD, professor and chair of the Department of Environmental Sciences and Engineering.
“His work has been used by state agencies to fill gaps in knowledge of pollutant distributions that otherwise would have required expensive sampling programs, and it is being used to estimate risks to human health in areas in which limited measurements have been made,” Aitken says.