Ying Sun

Ying Sun, assistant professor of statistics at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, won the 2016 Abdel El-Shaarawi Young Researcher (AEYR) Award from the International Environmetrics Society (TIES).

The award was established by the TIES board in 2002 to honor young statisticians who have made excellent contributions to the development of statistical and/or quantitative methods for environmental science research.

Sun received the award on July 18 during the annual Conference of the International Environmetrics Society in Edinburgh, Scotland, where she also gave a plenary talk.

TIES stated she was given the award for her “outstanding contributions to environmental statistics—in particular in the areas of spatio-temporal statistics, functional data analysis, and visualization—and for her distinguished service to the profession.”

“Sun’s strong accomplishment reflects the excellent work she is doing at KAUST,” said Mootaz Elnozahy, dean of KAUST’s Division on Computer, Electrical, and Mathematical Science and Engineering.

Sun earned her PhD in statistics from Texas A&M University in 2011, spent two years as a postdoctoral fellow at SAMSI and The University of Chicago, and worked as an assistant professor at The Ohio State University for one year before joining KAUST in 2014.

“The award is a significant recognition of my research in environmental statistics at KAUST,” Sun said. “I am very grateful for all the support and guidance I have received.”

A. Blanton Godfrey

The Statistics Division of the American Society for Quality (ASQ) is pleased to announce that A. Blanton Godfrey is the recipient of the 2016 William G. Hunter Award.

The Hunter award was established by the statistics division in 1987 to recognize the many contributions of its founding chair to promoting the use of applied statistics and statistical thinking. The attributes that characterize Hunter’s career—consultant, educator for practitioners, communicator, and integrator of statistical thinking into other disciplines—are used to help decide the recipient.

Godfrey is well known to many in industry and academia as a visionary leader in applied statistics and quality. He has made effective contributions to a wide array of application areas that include new technology development, manufacturing, product reliability and quality, and health care quality.

The Joseph D. Moore Distinguished University Professor in North Carolina State University’s College of Textiles, Godfrey also served as dean from 2000–2014. He was chair and CEO of Juran Institute, Inc. from 1987 to July 2000. From 1973 to 1987, he was a member of the technical staff at AT&T Bell Laboratories, the last five years as head of the quality theory and technology department.

Godfrey’s interests cover many areas of mathematical and applied statistics and quality management. He has had a long involvement in health care quality management and currently serves as a member and past chair of the board of directors for the Institute for Healthcare Improvement. He also contributed to the creation of the Malcolm Baldrige National Quality Award and served as a judge for the first three years of the award.

Godfrey has given seminars, consulted, or taught courses in more than 60 countries and his written materials have been translated, collectively, in more than 15 languages. He has personally worked with many of the top executives of leading companies throughout the world.

C. F. Jeff Wu

C. F. Jeff Wu, Coca-Cola Chair in Engineering Statistics and professor of Georgia Tech’s Stewart School of Industrial and Systems Engineering, has received the inaugural Akaike Memorial Lecture Award, sponsored by the Institute of Statistical Mathematics (ISM) and Japan Statistical Society (JSS). Wu gave the lecture September 5 in Kanazawa during the Joint Statistical Meetings of Japan.

The award is named after H. Akaike, who spent his whole career at ISM and served as its director general from 1986 to 1994. He is known for inventing the AIC (Akaike information criterion) for model selection.