Prepared by Michael Newton, COPSS Fisher Lecture Committee Chair, and Hugh Chipman, Acadia University
The 2011 Committee of Presidents of Statistical Societies (COPSS) asked C. F. Jeff Wu, professor and Coca Cola Chair in Engineering Statistics at Georgia Institute of Technology, to deliver the Fisher Lecture at the Joint Statistical Meetings in Miami Beach, Florida, on August 3 at 4:00 p.m.
Wu’s research contributions span the full range of statistics, from theory to application, and touch many applied domains, from sample surveys to nanotechnology. They are notable for their combination of novelty, technical strength, and far-reaching vision. He has made especially significant contributions to experimental design. As one of his supporters wrote, “In view of Professor Wu’s contribution to design of experiments, it is particularly fitting for him to deliver a lecture that honors R. A. Fisher, commonly regarded as father of the modern theory of experimental design.”
Wu was born in Taiwan and earned his BS degree in mathematics from National Taiwan University in 1971. After two years of compulsory military service, he came to the United States to study at the University of California, Berkeley and earned his PhD in statistics in 1976. He spent his formative years at the University of Wisconsin-Madison, from 1977–1988, then moved to the University of Waterloo as the first holder of the GM/NSERC Chair in Quality and Productivity from 1988–1993. He spent 10 years at the University of Michigan before joining Georgia Institute of Technology.
Wu is a highly accomplished scientist and mentor. He is a Fellow of the American Statistical Association, Institute of Mathematical Statistics, Institute for Operations Research and Management Sciences, and American Society for Quality and an elected member of the National Academy of Engineering. He has published one textbook, one research monograph, and more than 145 refereed papers in top journals. Wu also has given distinguished lectures at numerous universities and conferences around the world. He was previously recognized with the COPSS Presidents’ Award, and, in 2007, received the ASQ’s Shewart Medal for “outstanding technical leadership in the field of modern quality control.” His work on applications has received recognition on several occasions, including with the Wilcoxon Award and Jerome Sacks Award. Wu has served as the doctoral buy ativan pharmacy adviser for 35 PhD students, 31 of whom are now professors or research scientists at national labs.
Wu is well known for his wide-ranging research in the planning, analysis, and interpretation of statistical studies. Common themes in much of his work are the seed of a substantive scientific problem, development of novel statistical models, study of relevant statistical properties of the models, and development of algorithms that enable models to be estimated and used by scientists to optimize processes and make decisions. Wu has made numerous significant contributions to statistical theory, including definitive proof of convergence of the EM algorithm. His work on resampling methods rekindled research activity in the jackknife and bootstrap and their practical application in surveys. For instance, his work with Jon Rao on the bootstrap is now used for almost all Statistics Canada surveys.
Wu has made significant contributions to the theory of the design of experiments and, more broadly, to industrial statistics. He revolutionized experimental design by developing a modern system based on minimum aberration and nonregular designs. His work in industrial statistics has been at the forefront of a U.S. quality revolution that began in the 1980s. A common theme is the development of novel designs and models with a sound statistical basis, which can be used to efficiently extract maximal information in industrial problems when time is short, physical processes are complex, and every experimental run is costly. The genesis of much of this work comes from his extensive consulting collaborations with companies such as AT&T, Ford, GM, and Pfizer.
A hallmark of his industrial work is the use of statistical design and analysis to solve a substantive applied problem. This pattern continues to be evident in recent work that uses ideas from Genichi Taguchi’s robust parameter design to optimize the synthesis of nanostructures. His work on nanomaterials illustrates the type of research embodied by Fisher—close collaboration with scientific researchers, development of novel statistical methodology for the collection and analysis of data, and informed decisionmaking in the engineering process. These contributions mark Wu as an innovator in the Fisher style and make him a worthy choice to deliver the lecture named in Fisher’s honor.
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