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Plenary Speaker:
Jeff Wu
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TC.F. "Jeff" Wu
is a professor in ISyE and holds the Coca-Cola Chair in
Engineering Statistics. He was formerly the H. C. Carver Professor
of Statistics and Professor of Industrial and Operations
Engineering at the University of Michigan, Ann Arbor from 1993 -
July 2003, the GM/NSERC Chair in Quality and Productivity at the
University of Waterloo from 1988-1993, and before Waterloo, he
taught in the Statistics Department at the University of Wisconsin
from 1977-1988. He earned his BS in Mathematics from National
Taiwan University in 1971 and Ph.D. in Statistics from the
University of California, Berkeley (1973-1976). Dr. Wu joined
Georgia Tech in the summer of 2003. Dr. Wu's accomplishments include receiving the prestigious COPSS (Committee of Presidents of Statistical Societies) Presidents Award in 1987 which is presented annually to the best researcher under the age of 40. He has also been commissioned by five statistical societies, elected a Member (Academician) of Academia Sinica, and a Fellow of the American Society for Quality, of the Institute of Mathematical Statistics and of the American Statistical Association. Dr. Wu has won numerous awards, including the 1990 Wilcoxon Prize for the best practical application paper in Technometrics, the 1992 Brumbaugh Award for the single most important paper to quality control among the publications sponsored by the American Society for Quality Control, and the 1997 Jack Youden Prize for the best review paper in Technometrics. He was the 1998 P. C. Mahalanobis Memorial Lecturer at the Indian Statistical Institutes with widely cited research work and a listing as an “ISI Highly Cited Researcher” in 2002 on www.isihighlycited.com (ISI = Institute for Scientific Information). Dr. Wu's work is widely cited in professional journals as well as in magazines, including a feature article about his work in Canadian Business and a special issue of Newsweek on quality. He has served as editor or associate editor for several prestigious statistical journals like Annals of Statistics, Journal of American Statistical Association, Technometrics, and Statistica Sinica. Professor Wu has published more than 100 research articles in peer review journals. He has supervised 29 Ph.D.'s, out of which 14 are teaching in major research departments in statistics/engineering/business in US/Canada and two are senior VP in major US companies. He co-authors with Mike Hamada the award-winning book "Experiments: Planning, Analysis, and Parameter Design Optimization" (Wiley, 2000, 638 pages). |
A
Modern Theory of Factorial Designs
A modern theory of factorial designs is outlined that attempts to
encompass the major work in the last two decades. Traditionally,
regular orthogonal designs, include the 2^{n-k} and 3^{n-k} series,
have been used for factorial experiments. A central issue in
conducting factorial experiments is the optimal assignment of
factors and interactions to columns of the design. This is equivalent
to the choice of fractions according to some optimality criterion. The
minimum aberration (MA) criterion (and related criteria) has emerged
as the
major criterion for this problem. Major results and techniques,
especially the use of complementary sets, will be presented for
finding MA s^{n-k} designs, s being a prime power. The problem becomes
harder if the factors cannot be treated symmetrically (e.g., blocking
or split-plot structure, and robust parameter designs.) Extensions of
such results to nonregular orthogonal designs will be briefly
outlined. Many of the results in this talk are available from the
forthcoming book "A Modern Theory of Factorial Designs" by Rahul
Mukerjee and C. F. Jeff Wu (2000, Springer).
12th Annual Conference of the Forum for Interdisciplinary Mathematics (FIM XII)