Home » Member News, Section News, Statistics and the Environment

Section Congratulates Award Winners

1 October 2010 No Comment
Jun Zhu, ENVR Publications Chair

During this year’s JSM in Vancouver, BC, Section Chair Dale Zimmerman presented several awards during the ENVR business meeting/mixer.

Student Paper Competition

David Dail, a PhD student in statistics at Oregon State University, won the student paper competition with “Models for Estimating Population Size from Repeated Counts of an Open Population”

Ying Sun, a PhD student in statistics at Texas A&M University, was the runner-up for “Functional Boxplots for Complex Space-Time Data Visualization”

JSM Presentation Award

Joel Reynolds, a regional biometrician at the U.S. Fish and Wildlife Service in Anchorage, Alaska, won the 2009 JSM Presentation Award for “Effective and Efficient Monitoring of Steller’s Eiders at Izembek Lagoon, Alaska: Barriers and Pitfalls.”

Sandrah Eckel is the winner of ENVR’s 2010 JSM Presentation Award for “Modification by Frailty Status of the Respiratory Health Effect of Air Pollution in Older Adults.” Eckel is a postdoc in the division of biostatistics, department of preventive medicine, at the Keck School of Medicine, University of Southern California. She earned her PhD in biostatistics from The Johns Hopkins University in 2009. This award will be presented to Eckel at JSM 2011 in Miami Beach, Florida.

Distinguished Achievement Award

Marc G. Genton of Texas A&M University won the section’s Distinguished Achievement Award for his theoretical, methodological, and computational contributions to robust statistics; spatial and spatiotemporal statistics; time series; and multivariate analysis with diverse applications, including wildfires, wind energy, and precipitation fields, as well as his contributions to educating the next generation of environmental statisticians.

Victor De Oliveira of The University of Texas at San Antonio won the Distinguished Achievement Award for his contributions to the spatial analysis of environmental data, including modeling and prediction of non-Gaussian random fields, censored data, and Bayesian geostatistics, as well as his service to the profession.

1 Star2 Stars3 Stars4 Stars5 Stars (No Ratings Yet)

Comments are closed.