Ph.D., University of California, Berkeley

B.Sc., National Taiwan University

C. F. Jeff Wu is the X.Q. Deng Presidential Chair Professor in the School of Data Science of The Chinese University of Hong Kong, Shenzhen.

He was elected a Member of the National Academy of Engineering (2004), and a Member (Academician) of Academia Sinica (2000). A Fellow of the Institute of Mathematical Statistics (1984), the American Statistical Association (1985), the American Society for Quality (2002), and the Institute for Operations Research and Management Sciences (2009). He received the COPSS (Committee of Presidents of Statistical Societies) Presidents' Award in 1987, which was given to the best researcher under the age of 40 per year and was commissioned by five statistical societies. His other major awards include the 2011 COPSS Fisher Lecture, the 2012 Deming Lecture (plenary lectures during the annual Joint Statistical Meetings), the Shewhart Medal (2008) from ASQ, and the Pan Wenyuan Technology Award (2008). In 2016 he received the (inaugural) Akaike Memorial Lecture Award. In 2017 he received the George Box Medal from ENBIS. In 2020 he won The Class of 1934 Distinguished Professor Award and the Sigma Xi Monie A. Ferst Award both at Georgia Institute of Technology. He has won numerous other awards, including the Wilcoxon Prize, the Brumbaugh Award (twice), the Jack Youden Prize (twice), and the Honoree of the 2008 Quality and Productivity Research Conference. He was the 1998 P. C. Mahalanobis Memorial Lecturer at the Indian Statistical Institutes and an Einstein Visiting Professor at the Chinese Academy of Sciences (CAS). He is an Honorary Professor at several institutions, including the CAS and National Tsinghua University. He received an honorary doctor (honoris causa) of mathematics at the University of Waterloo in 2008.

He was formerly the H. C. Carver Professor of Statistics and Professor of Industrial and Operations Engineering at the University of Michigan, 1993-2003 and the GM/NSERC Chair in Quality and Productivity at the University of Waterloo in 1988-1993. In his 1997 inaugural lecture for the Carver Chair, he coined the term data science and advocated that statistics be renamed data science and statistician to data scientist. Before Waterloo, he taught in the Statistics Department at the University of Wisconsin from 1977-1988. He got his BS in Mathematics from National Taiwan University in 1971 and Ph.D. in Statistics from the University of California, Berkeley (1973-1976).

His 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 major statistical journals like Annals of Statistics, Journal of American Statistical Association, Technometrics, and Statistica Sinica. Professor Wu has published more than 185 research articles in peer review journals. He has supervised 52 Ph.D.'s, out of which more than half are teaching in major research departments or institutions in statistics, engineering, or business in US/Canada/Asia/Europe. Among them, there are 28 Fellows of ASA, IMS, ASQ, IAQ and IIE, three editors of Technometrics, one editor of JQT, and one is a Fellow of Royal Society of Canada (FRSC). He co-authors with Mike Hamada the book "Experiments: Planning, Analysis, and Optimization" (Wiley, 2nd Ed, 2009, 716 pages) and with R. Mukerjee the book "A Modern Theory of Factorial Designs" (Springer, 2006).

1. C. F. J. Wu (1983). On the convergence properties of the EM algorithm. Annals of Statistics, 11, 95-103.
2. C. F. J. Wu and M. S. Hamada (2021). Experiments: Planning, Analysis, and Optimization. Third Edition. John Wiley (700 pages). (First Edition 2000, Second Edition 2009).
3. C. F. J. Wu (1986). Jackknife, bootstrap and other resampling methods in regression analysis (with discussion). Annals of Statistics, 14, 1261-1350.
4. J. N. K. Rao and C. F. J. Wu (1988). Resampling inference with complex survey data. Journal of the American Statistical Association, 83, 231-241.
5. J. N. K. Rao, C. F. J. Wu and K. Yue (1992). Some recent work on resampling methods for complex surveys. Survey Methodology, 18, 209-217.
6. C. F. J. Wu (1981). Asymptotic theory of nonlinear least squares estimation. Annals of Statistics, 9, 501-513.
7. A. C. Shoemaker, K. L. Tsui and C. F. J. Wu (1991). Economical experimentation methods for robust design. Technometrics, 33, 415-427.
8. M. Hamada and C. F. J. Wu (1992). Analysis of designed experiments with complex aliasing. Journal of Quality Technology, 24, 130-137.
9. P. Z. G. Qian and C. F. J. Wu (2008). Bayesian hierarchical modeling for integrating low-accuracy and high-accuracy experiments. Technometrics, 50, 192-204.
10. H. Xu and C. F. J. Wu (2001). Generalized minimum aberration for asymmetrical fractional factorial designs. Annals of Statistics, 29, 1066-1077.
11. R. Mukerjee and C. F. J. Wu (2006). A Modern Theory of Factorial Designs (230 pages), Springer.
12. C. F. J. Wu (1981). On the robustness and efficiency of some randomized designs. Annals of Statistics, 9, 1168-1177.
13. C. F. J. Wu (1985). Efficient sequential designs with binary data. Journal of the American Statistical Association, 80, 974-984.
14. J. Shao and C. F. J. Wu (1989). A general theory for jackknife variance estimation. Annals of Statistics, 17, 1176-1197.
15. B. Tang and C. F. J. Wu (1996). Characterization of minimum aberration 2^n-k designs in terms of their complementary designs. Annals of Statistics, 24, 2549-2559.
16. V. R. Joseph and C. F. J. Wu (2004). Failure amplification method: an information maximization approach to categorical response optimization (with discussions). Technometrics, 46, 1-31. (winner of the Jack Youden Prize).
17. P. Z. G. Qian, H.Wu, and C. F. J. Wu (2008). Gaussian process models for computer experiments with qualitative and quantitative factors. Technometrics, 50, 383-396.
18. P. Z. G. Qian and C. F. J. Wu (2009). Sliced space-filling designs. Biometrika, 96, 945-956.
19. C. F. J.Wu and Y. Tian (2014). Three-phase optimal design of sensitivity experiments (with discussions). J. Statistical Planning and Inference, 149, 1-32.
20. Rui Tuo, C. F. J. Wu and Dan Yu (2014). Surrogate modeling of computer experiments with different mesh densities. Technometrics, 56, 372-380.
21. C. F. J. Wu (2015). Post-Fisherian experimentation: from physical to virtual. Journal of American Statistical Association, 110, 612-620. (based on the 2011 Fisher Lecture.)
22. Rui Tuo and C. F. J. Wu (2015). Efficient calibration for imperfect computer models. Ann. Stat., 43, 2331-2352.
23. Rui Tuo and C. F. J. Wu (2016). A theoretical framework for calibration in computer models: parametrization estimation and convergence properties. SIAM/ASA Journal on Uncertainty Quantification, 4, 767-795.
24. Simon Mak, C. L. Sung, S. T. Yeh, X. Wang, Y. H. Chang, V. R. Joseph, V. Yang and C. F. J. Wu (2018). An efficient surrogate model for emulation and physics extraction of large eddy simulations. Journal of American Statistical Association, 113, 1443-1456.
25. Simon Mak and C. F. J. Wu (2019). cmenet: a new method for bi-level variable selection of conditional main effects. Journal of American Statistical Association, 114, 844-856.
26. Z. Chen, S. Mak and C. F. J. Wu (2024). A hierarchical expected improvement method for Bayesian optimization. Journal of American Statistical Association, 119(546), 1619-1632.