Welcome to
C. F. Jeff Wu WEBSITE
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).
A. PUBLISHED BOOKS, BOOK CHAPTERS, AND EDITED VOLUMES
1. G. E. P. Box, T. Leonard and C. F. J. Wu (1983, Joint Editors). Scientific Inference, Data Analysis and Robustness. Academic Press.
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).
(Chinese translation 2003, full book; Japanese translation, 2018, two chapters)
3. R. Mukerjee and C. F. J. Wu (2006). A Modern Theory of Factorial Designs (230 pages), Springer.
4. J. Fan, Y. Ritov and C. F. J. Wu (2013). Selected Works of Peter Bickel. Springer (568 pages).
B. REFEREED PUBLICATIONS AND SUBMITTED ARTICLES
Published
1. C. F. J. Wu (1973). A note on convergence rate of the strong law of large numbers. Bulletin of the Institute of Mathematics, Academia Sinica, 1, 121-124.
2. C. F. J. Wu (1978). Some algorithmic aspects of the theory of optimal designs. Annals of Statistics, 6, 1286-1301.
3. C. F. J. Wu and H. P. Wynn (1978). The convergence of general step-length algorithms for regular optimum design criteria. Annals of Statistics, 6, 1273-1285.
4. C. F. J. Wu (1978). Some iterative procedures for generating nonsingular optimal designs. Communications in Statistics, Series A, 7, Special Issue on Optimal Design Theory, 1399-1412.
5. C. F. J. Wu (1980). Characterizing the consistent directions of least squares estimates. Annals of Statistics, 8, 789-801.
6. C. F. J. Wu (1980). On some ordering properties of the generalized inverses of nonnegative definite matrices. Linear Algebra and its Applications, 32, 49-60.
7. C. S. Cheng and C. F. J. Wu (1981). Balanced repeated measurements designs. Annals of Statistics, 8, 1272-1283. (Correction, 1983, Volume 11, 349).
8. C. F. J. Wu (1981). Iterative construction of nearly balanced assignments I: categorical covariates. Technometrics, 23, 37-44.
9. A. J. Scott and C. F. J. Wu (1981). On the asymptotic distributions of ratio and regression estimators. Journal of the American Statistical Association, 76, 98-102.
10. R. Bohrer, W. Chow, R. Faith, V. M. Joshi and C. F. J. Wu (1981). Multiple decision rules for factorial simple effects: Bonferroni wins again! Journal of the American Statistical Association, 76, 119-124.
11. C. F. J. Wu (1981). Asymptotic theory of nonlinear least squares estimation. Annals of Statistics, 9, 501-513.
12. C. S. Cheng and C. F. J. Wu (1981). Nearly balanced incomplete block designs. Biometrika, 68, 493-500.
13. C. F. J. Wu (1981). On the robustness and efficiency of some randomized designs. Annals of Statistics, 9, 1168-1177.
14. C. F. J. Wu (1982). Estimation of variance of the ratio estimator. Biometrika, 69, 183-189.
15. C. F. J. Wu (1982). Some algorithms for concave regression and isotonic regression. TIMS Studies in the Management Sciences, 19, (Optimization in Statistics) 105-116, North Holland.
16. L. Y. Deng and C. F. J. Wu (1983). Estimation of variance of the ratio estimator: an empirical study. Scientific Inference, Data Analysis, and Robustness (G. E. P. Box et al., Ed.), 245-277, Academic Press.
17. C. F. J. Wu (1983). On the convergence properties of the EM algorithm. Annals of Statistics, 11, 95-103.
18. J. F. Soares and C. F. J. Wu (1983). Some restricted randomization rules in sequential designs. Communications in Statistics, Series A, 12, 2017-2034.
19. S. G. Wang and C. F. J. Wu (1983). Further results on the consistent directions of least squares estimators. Annals of Statistics, 11, 1257-1262.
20. C. Stepniak, S. G. Wang and C. F. J. Wu (1984). Comparison of linear experiments with known covariances. Annals of Statistics, 12, 358-365.
21. S. G. Wang and C. F. J. Wu (1984). Consistent directions of the least squares estimator in linear models. Statistical Theory and Data Analysis (K. Matusita, ed.), 763-782, North Holland.
22. C. F. J. Wu (1984). Estimation in systematic sampling with supplementary observations. Sankhyā, Series B, 46, 306-315.
23. J. F. Soares and C. F. J. Wu (1985). Optimality of random allocation design for the control of accidental bias in sequential experiments. Journal of Statistical Planning and Inference, 11, 81-87.
24. C. F. J. Wu (1985). Variance estimation for the combined ratio and combined regression estimators. Journal of the Royal Statistical Society, Series B, 47, 147-154.
25. Ping Cheng and C. F. J. Wu (1985). Discussion of “Projection Pursuit” by P. J. Huber. Annals of Statistics, 13, 490-493.
26. J. N. K. Rao and C. F. J. Wu (1985). Inference from stratified samples: second order analysis of three methods for nonlinear statistics. Journal of the American Statistical Association, 80, 620-630.
27. C. F. J. Wu (1985). Efficient sequential designs with binary data. Journal of the American Statistical Association, 80, 974-984.
28. T. Kariya and C. F. J. Wu (1985). On the nonsingularity of principal submatrices of a random orthogonal matrix. Journal of Statistical Planning and Inference, 12, 353-357.
29. C. F. J. Wu (1985). Asymptotic inference from sequential design in a nonlinear situation. Biometrika, 72, 553-558.
30. I. Ford, D. M. Titterington and C. F. J. Wu (1985). Inference and sequential design. Biometrika, 72, 545-551.
31. C. F. J. Wu (1986). Maximum likelihood recursion and stochastic approximation in sequential designs. Adaptive Statistical Procedures and Related Topics (J. Van Ryzin, ed.), IMS Monograph Series, 8, 298-313.
32. S. K. Tse and C. F. J. Wu (1986). Comparison of the dichotomous and polytomous response models. Journal of Statistical Planning and Inference, 14, 187-202.
33. C. F. J. Wu (1986). Jackknife, bootstrap and other resampling methods in regression analysis (with discussion). Annals of Statistics, 14, 1261-1350.
34. M. Hamada and C. F. J. Wu (1986). Should accumulation analysis and related methods be used for industrial experiments? A discussion of “Testing in industrial experiments with ordered categorical data” by V. N. Nair. Technometrics, 28, 302-306.
35. L. Y. Deng and C. F. J. Wu (1987). Estimation of variance of the regression estimator. Journal of the American Statistical Association, 82, 568-576.
36. J. Shao and C. F. J. Wu (1987). Heteroscedasticity-robustness of jackknife variance estimators in linear models. Annals of Statistics, 15, 1563-1579.
37. G. Box, R. Kackar, V. Nair, M. Phadke, A. Shoemaker and C. F. J. Wu (1988). Quality practice in Japan. Quality Progress, 37-41.
38. C. F. J. Wu, D. Holt and D. Holmes (1988). On the effect of two-stage sampling on the F statistic. Journal of the American Statistical Association, 83, 150-159.
39. 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.
40. J. Korvar, J. N. K. Rao and C. F. J. Wu (1988). Bootstrap and other methods to measure errors in survey estimates. Canadian Journal of Statistics, 16, Supplement, 25-45.
41. K. L. Tsui, N. Jewell and C. F. J. Wu (1988). A nonparametric approach to the truncated regression problem. Journal of the American Statistical Association, 83, 785-792.
42. C. F. J. Wu (1988). Optimal design for percentile estimation of a quantal response curve. Optimal Design and Analysis of Experiments (Y. Dodge et al., Ed.) 213-223, North Holland.
43. R. J. Carroll, C. F. J. Wu and D. Ruppert (1988). The effect of estimating weights in generalized least squares. Journal of the American Statistical Association, 83, 1045-1054.
44. J. Shao and C. F. J. Wu (1989). A general theory for jackknife variance estimation. Annals of Statistics, 17, 1176-1197.
45. C. F. J. Wu (1989). Construction of 
designs via a grouping scheme. Annals of Statistics, 17, 1880-1885.
46. M. Hamada and C. F. J. Wu (1990). A critical look at accumulation analysis and related methods. Technometrics, 32, 119-162. (discussion paper) (winner of the Frank Wilcoxon Prize).
47. S. S. Mao, F. S. Ma, and C. F. J. Wu (1990). Sequential elimination of levels: an investigation method using orthogonal arrays. Chinese Journal of Applied Probability and Statistics, 6, 185-204. (in Chinese with English abstract).
48. Xiquan Shi, C. F. J. Wu and Jiahua Chen (1990). Weak and strong representations for quantile processes from finite populations with application to simulation size in resampling inference. Canadian Journal of Statistics, 18, 141-148.
49. C. F. J. Wu, S. S. Mao and F. S. Ma (1990). SEL: A search method based on orthogonal arrays. Statistical Design and Analysis of Industrial Experiments (S. Ghosh, ed.), 279-310, Marcel Dekker.
50. C. F. J. Wu (1990). On the asymptotic properties of the jackknife histograms. Annals of Statistics, 18, 1438-1452.
51. M. S. Hamada and C. F. J. Wu (1991). Analysis of censored data from highly fractionated experiments. Technometrics, 33, 25-38.
52. C. F. J. Wu (1991). Balanced repeated replications based on mixed orthogonal arrays. Biometrika, 78, 181-188.
53. Jiahua Chen and C. F. J. Wu (1991). Some results on 
fractional factorial designs with minimum aberration or optimal moments. Annals of Statistics, 19, 1028-1041.
54. J. C. Wang and C. F. J. Wu (1991). An approach to the construction of asymmetrical orthogonal arrays. Journal of the American Statistical Association, 86, 450-456.
55. A. C. Shoemaker, K. L. Tsui and C. F. J. Wu (1991). Economical experimentation methods for robust design. Technometrics, 33, 415-427.
56. C. F. J. Wu, R. Zhang and R. Wang (1992). Construction of asymmetrical orthogonal arrays of the type 
. Statistica Sinica, 2, 203-219.
57. I. Ford, B. Torsney and C. F. J. Wu (1992). The use of canonical form in the construction of locally optimum designs for nonlinear problems. Journal of the Royal Statistical Society, Ser. B, 54, 569-583.
58. C. F. J. Wu and Youyi Chen (1992). A graph-aided method for planning two-level experiments when certain interactions are important. Technometrics, 34, 162-175.
59. R. Leon and C. F. J. Wu (1992). A theory of performance measures in parameter design. Statistica Sinica, 2, 335-358.
60. M. Hamada and C. F. J. Wu (1992). Analysis of designed experiments with complex aliasing. Journal of Quality Technology, 24, 130-137. (winner of the Brumbaugh Award). (Reproduced and included in Volume 7 of The Best on Quality, International Academy for Quality, 1996, ASQC Quality Press.)
61. J. Shao and C. F. J. Wu (1992). Asymptotic properties of the balanced repeated replication method for sample quantiles. Annals of Statistics, 20, 1571-1593.
62. J. C. Wang and C. F. J. Wu (1992). Nearly orthogonal arrays with mixed levels and small runs. Technometrics, 34, 409-422.
63. J. Armstrong and C. F. J. Wu (1992). A sample allocation method for two-phase survey design. Survey Methodology, 18, 251-262.
64. 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.
65. D. X. Sun and C. F. J. Wu (1993). Statistical properties of Hadamard matrices of order 16. In Quality Through Engineering Design (W. Kuo, Ed.), 169-179, Elsevier.
66. J. Chen, D. X. Sun and C. F. J. Wu (1993). A catalogue of two-level and three-level fractional factorial designs with small runs. International Statistical Review, 61, 131-145.
67. A. Miller, R. Sitter, C. F. J. Wu and D. Long (1993). Are large Taguchi-style experiments necessary? A reanalysis of gear and pinion data. Quality Engineering, 6, 21-37.
68. C. F. J. Wu and R. Zhang (1993). Minimum aberration designs with two-level and four-level factors. Biometrika, 80, 203-209.
69. R. Sitter and C. F. J. Wu (1993). On the accuracy of Fieller intervals for binary response data. Journal of the American Statistical Association, 88, 1021-1025.
70. C. F. J. Wu (1993). Construction of supersaturated designs through partially aliased interactions. Biometrika, 80, 661-669.
71. R. Sitter and C. F. J. Wu (1993). Optimal designs for binary response experiments. Scandinavian Journal of Statistics, 20, 329-341.
72. L. Deng, M. Aksmanovic, D. X. Sun and C. F. J. Wu (1994). Speech recognition using hidden Markov models with polynomial regression functions as nonstationary states. IEEE Transactions on Speech and Audio Processing, 2, 507-520.
73. D. X. Sun, L. Deng and C. F. J. Wu (1994). State-dependent time warping in the trended hidden Markov model. Signal Processing, 39, 263-275.
74. D. X. Sun and C. F. J. Wu (1994). Interaction graphs for three-level fractional factorial designs. Journal of Quality Technology, 26, 297-307.
75. J. C. Wang and C. F. J. Wu (1995). A hidden projection property of Plackett-Burman and related designs. Statistica Sinica, 5, 235-250.
76. M. Hamada and C. F. J. Wu (1995). The treatment of related experimental factors by sliding levels. Journal of Quality Technology, 27, 45-55.
77. M. Hamada and C. F. J. Wu (1995). Analysis of censored data from fractionated experiments: a Bayesian approach. Journal of the American Statistical Association, 90, 467-477.
78. C. M. Anderson and C. F. J. Wu (1995). Measuring location effects from factorial experiments with a directional response. International Statistical Review, 63, 345-363.
79. R. Mukerjee and C. F. J. Wu (1995). On the existence of saturated and nearly saturated asymmetrical orthogonal arrays. Annals of Statistics, 23, 2102-2115.
80. C. M. Anderson and C. F. J. Wu (1996). Dispersion measures and analysis for factorial directional data with replicates. Applied Statistics, 45, 47-61.
81. A. Miller and C. F. J. Wu (1996). Commentary on Taguchi’s parameter design with dynamic characteristics. Quality and Reliability Engineering International, 12, 75-78.
82. A. Miller and C. F. J. Wu (1996). Parameter design for signal-response system: a different look at Taguchi’s dynamic parameter design. Statistical Science, 11, 122-136.
83. B. Tang and C. F. J. Wu (1996). Characterization of minimum aberration 
designs in terms of their complementary designs. Annals of Statistics, 24, 2549-2559.
84. Z. Ying and C. F. J. Wu (1997). An asymptotic theory of sequential designs based on maximum likelihood recursions. Statistica Sinica, 7, 75-91.
85. B. Tang and C. F. J. Wu (1997). A method for constructing supersaturated designs and its 
optimality. Canadian Journal of Statistics, 25, 191-201.
86. W. W. Li and C. F. J. Wu (1997). Columnwise-pairwise algorithms with applications to the construction of supersaturated designs. Technometrics, 39, 171-179.
87. C. Y. Suen, H. Chen and C. F. J. Wu (1997). Some identities on 
designs with application to minimum aberration designs. Annals of Statistics, 25, 1176-1188.
88. D. X. Sun, C. F. J. Wu and Y. Chen (1997). Optimal blocking schemes for 
and 
designs. Technometrics, 39, 298-307. (winner of the Jack Youden Prize).
89. H. Chipman, M. Hamada and C. F. J. Wu (1997). A Bayesian variable selection approach for analyzing designed experiments with complex aliasing. Technometrics, 39, 372-381.
90. P. R. Moorhead and C. F. J. Wu (1998). Cost-driven parameter design. Technometrics, 40, 111-119.
91. C. F. J. Wu and Y. Ding (1998). Construction of response surface designs for qualitative and quantitative factors. Journal of Statistical Planning and Inference, 71, 331-348.
92. W. W. Li and C. F. J. Wu (1999). An integrated method of parameter design and tolerance design. Quality Engineering, 11, 417-425.
93. R. Sitter and C. F. J. Wu (1999). Two-stage designs of quantal response studies. Biometrics, 55, 396-402.
94. F. Tsung, J. Shi and C. F. J. Wu (1999). Joint monitoring of PID controlled processes. Journal of Quality Technology, 31, 275-285.
95. R. Mukerjee and C. F. J. Wu (1999). Blocking in regular fractional factorials: a projective geometric approach. Annals of Statistics, 27, 1256-1271.
96. J. Berube and C. F. J. Wu (2000). Signal-to-noise ratio and related measures in parameter design optimization: an overview. Sankhya, Series B, 62, 417-432.
97. R. Mukerjee and C. F. J. Wu (2001). Minimum aberration designs for mixed factorials in terms of complementary sets. Statistica Sinica, 11, 225-239.
100. S. W. Cheng and C. F. J. Wu (2001). Factor screening and response surface exploration (with discussion). Statistica Sinica, 11, 553-604.
101. H. Xu and C. F. J. Wu (2001). Generalized minimum aberration for asymmetrical fractional factorial designs. Annals of Statistics, 29, 1066-1077.
102. S. W. Cheng and C. F. J. Wu (2002). Choice of optimal blocking schemes in two-level and three-level designs. Technometrics, 44, 269-277.
103. V. R. Joseph and C. F. J. Wu (2002). Operating window experiments: a novel approach to quality and reliability improvement. J. Quality Technology, 34, 345-354.
104. V. R. Joseph and C. F. J. Wu (2002). Robust parameter design of multiple target systems. Technometrics, 44, 338-346.
105. L. Huwang, C. F. J. Wu and C. H. Yen (2002). The idle column method: construction, properties and comparisons. Technometrics, 44, 347-355.
106. H. Xu, P. Wu, C. F. J. Wu, C. Tidwell and Y. Wang (2002). A smooth response surface algorithm for constructing gene regulatory network. Physiological Genomics, 11, 11-20.
107. Huaiqing Wu and C. F. J. Wu (2002). Clear two-factor interactions and minimum aberration. Annals of Statistics, 30, 1496-1511.
108. V. R. Joseph and C. F. J. Wu (2002). Performance measures in dynamic parameter design. Journal of Japanese Quality Engineering Society, 10, 82-86.
109. S. W. Cheng, C. F. J. Wu and H. Wu (2003). Finding defining generators with extreme lengths. Journal of Statistical Planning and Inference, 113, 315-321.
110. C. F. J. Wu and Y. Zhu (2003). Optimal selection of single arrays for parameter design experiments. Statistica Sinica, 13, 1179-1199.
111. 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).
112. H. Xu, Cheng. S. W, and C. F. J. Wu (2004). Optimal projective three-level designs for factor screening and interaction detection. Technometrics, 46, 280-292.
113. X. Qu and C. F. J. Wu (2005). One-factor-at-a-time designs of resolution V. Journal of Statistical Planning and Inference, 131, 407-416.
114. H. Xu and C. F. J. Wu (2005). Construction of optimal multi-level supersaturated designs. Annals of Statistics, 33, 2811-2836.
115. G. Dyson and C. F. J. Wu (2006). MAOSA: A new procedure for detection of differential gene expression. Statistical Methodology, 3, 42-54.
116. Z. Qian, C. Seepersad, R. Joseph, J. Allen and C. F. J. Wu (2006). Building surrogate models based on detailed and approximate simulations. ASME Journal of Mechanical Design, 128, 668-677.
117. A. Mandal, C. F. J. Wu and K. Johnson (2006). SELC: Sequential elimination of level combinations by means of modified genetic algorithms. Technometrics, 48, 273-283.
118. T. Dasgupta and C. F. J. Wu (2006). Robust parameter design with feedback control. Technometrics, 48, 349-360.
119. S. W. Cheng, C. F. J. Wu and L. Huwang (2006). Statistical modeling for experiments with sliding levels. In Time Series and Related Topics. IMS Lecture Notes-Monograph Series, Volume 52, 245-256.
120. Y. Zhu and C. F. J. Wu (2007). Structure functions for general sl - m design and blocked regular (sl – m, sr ) design and their complementary designs. Statistica Sinica, 17, 1237-1257.
121. V. R. Joseph, Y. Tian and C. F. J. Wu (2007). Adaptive designs for stochastic root-finding. Statistica Sinica, 47, 1549-1565.
122. A. Mandal, K. Johnson, C. F. J. Wu and D. Bornemeier (2007). Identifying promising compounds in drug discovery: genetic algorithms and some new statistical techniques. Journal of Chemical Information and Modeling, 47, 981-988.
123. T. Dasgupta, C. Ma, V. R. Joseph, Z. L. Wang and C. F. J. Wu (2008). Statistical modeling and analysis for robust synthesis of nanostructures. Journal of American Statistical Association, 103, 594-603.
124. G. Dyson and C. F. J. Wu (2008). ICI: A new approach to explore between-cluster relationships with applications to gene expression data. Journal of Biopharmaceutical Statistics, 18, 244-255.
125. 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.
126. S. L. Jeng, Joseph, V. R. and C. F. J. Wu (2008). Modeling and analysis strategies for failure amplification method. Journal of Quality Technology, 40, 128-139.
127. R. Mukerjee, P. Z. G. Qian and C. F. J. Wu (2008). On the existence of nested orthogonal arrays. Discrete Mathematics, 308, 4635-4642.
128. 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.
129. Y. Hung, V. Zarnitsyna, Y. Zhang, C. Zhu, and C. F. J. Wu (2008). Binary time series modeling with
application to adhesion frequency experiments. Journal of the American Statistical Association, 103, 1248-
1259.
130. P. Z. G. Qian, B. Tang and C. F. J. Wu (2009). Nested space-filling designs for experiments with two levels
of accuracy. Statistica Sinica, 19, 287-300.
131. X. Deng, V. R. Joseph, W. Mai, Z. L. Wang, and C. F. J. Wu, (2009). A statistical approach to quantifying
the elastic deformation of nanomaterials, Proc. Nat. Acad. Sci., 106(29), 11845-11850.
132. S. Xu, N. Adiga, S. Ba, T. Dasgupta, C. F. J. Wu and Z. L. Wang (2009). Optimizing and improving the growth quality of ZnO nanowire arrays guided by statistical design of experiments. American Chemical Society, Nano, 3(7), 1803-1812.
133. M. Ai, X. Xu and C. F. J. Wu (2010). Optimal blocking and foldover plans for regular two-level designs. Statistica Sinica, 20, 183-207.
134. V. R. Joseph, M. Ai and C. F. J. Wu (2009). Bayesian-inspired optimal mixed two- and four-level designs. Biometrika, 96(1), 95-106.
135. A. Mandal, P. Ranjan and C. F. J. Wu (2009). G-SELC: optimization by sequential elimination of level combinations using genetic algorithms and gaussian processes. Ann. Applied Statistics, 3, 398-421.
136. P. Z. G. Qian, M. Ai and C. F. J. Wu (2009). Construction of nested space-filling designs. Ann. Stat., 37, 3616-43.
137. X. Deng, V. R. Joseph, A. Sudjianto and C. F. J. Wu (2009). Active learning via sequential design with applications to detection of money laundering. Journal of the American Statistical Association, 104(487), 969-981.
138. P. Z. G. Qian and C. F. J. Wu (2009). Sliced space-filling designs. Biometrika, 96, 945-956.
139. T. Dasgupta, A. Miller and C. F. J. Wu (2010). Robust design, modeling and analysis of measurement systems. Technometrics, 52, 80-93.
140. W. Tan, I. C. Ume, Y. Hung and C. F. J. Wu (2010). Effects of warpage on fatigue reliability of solder bumps: experimental and analytical studies. IEEE Transactions on Advanced Packaging, 33, 314-322.
141. J. Zhong, J. Shi, and C. F. J. Wu (2010). Design of experiment-based Automatic process controller with consideration of model and observation. IEEE Transactions on Automation Science and Engineering, 7, 266 – 273.
142. Y. Hung, Y. Amemiya, and C. F. J. Wu (2010). Probability-based Latin hypercube designs for slid-rectangular regions. Biometrika, 97, 961-968.
143. J. Song, H. Xie, W. Wu, V. R. Joseph, C. F. J. Wu, and Z. L. Wang (2010). Robust optimization of the output voltage of nanogenerators by statistical design of experiments. Nano Research, 3, 613-619.
144. R. B. Chen, W. Wang and C. F. J. Wu (2011). Building surrogates with overcomplete bases in a computer experiment for bistable laser diodes. IIE Transactions (Quality and Reliability Engineering), 43, 39-53.
145. Matthias Tan and C. F. J. Wu (2011). Generalized selective assembly. IIE Transactions (Quality and Reliability Engineering), 44, 27-42.
146. T. Dasgupta, N. Adiga and C. F. J. Wu (2011). Another look at Dorian Shainin's variable search technique, Journal of Quality Technology, 43, 273-287.
147. Matthias Tan and C. F. J. Wu (2012). Robust design optimization with quadratic loss derived from Gaussian process models. Technometrics, 54, 51-63.
148. R. Tuo, P. Qian, and C. F. J. Wu (2013). A Brown motion model for stochastic simulation with tunable precision. Comment on “Quantile-based optimization of noisy computer experiments with tunable precision” by Picheny et al. Technometrics, 55, 29-31.
149. S. P. Xiong, P. Z. G. Qian and C. F. J. Wu (2013). Sequential design and analysis of high-accuracy and low-accuracy computer codes. Technometrics, 55, 37-46.
150. L. Ju, Y. D. Wang, Y. Hung, C. F. J. Wu and C. Zhu (2013). An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data. Bioinformatics, 29, 1511-1518.
151. Matthias Tan and C. F. J. Wu (2013). A Bayesian approach for model selection in fractionated split plot experiments with applications in robust parameter design. Technometrics, 55, 359-372.
152. Y. Hung, Y. Wang, V. Zarnitsyna, C. Zhu and C. F. J. Wu (2013). Hidden Markov models with applications in cell adhesion experiments. Journal of American Statistical Association, 108, 1469-1479.
153. Y. Sun, Y. Heo, M. H. Y. Tan, H. Xie, C. F. J. Wu, and G. Augenbroe (2014). Uncertainty quantification of microclimate variables in building energy models. Journal of Building Performance Simulation, 7, 17-32.
154. 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.
155. C. Peng and C. F. J. Wu (2014). On the choice of nugget in kriging modeling for deterministic computer experiments. Journal of Computational and Graphical Statistics, 23, 151-168.
156. A. Sabbaghi, T. Dasgupta and C. F. J. Wu (2014). Indicator functions and the algebra of the linear-quadratic parametrization. Biometrika, 101, 351-363.
157. Rui Tuo, C. F. J. Wu and Dan Yu (2014). Surrogate modeling of computer experiments with different mesh densities. Technometrics, 56, 372-380.
158. H. Xie, S. P. Xiong, P. Z. G. Qian and C. F. J. Wu (2014). General sliced Latin hypercube designs. Statistica Sinica, 24, 1239-1256.
159. Y. Sun, L. Gu, C. F. J. Wu, and G. Augenbroe (2014). Exploring HVAC system sizing under uncertainty. Energy and Buildings, 81, 243-252.
160. R. Joseph, T. Dasgupta, R. Tuo and C. F. J. Wu (2015). Sequential exploration of complex surfaces using minimum energy designs. Technometrics, 57, 64-74.
161. 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.)
162. Y. Sun, H. Su, C. F. J. Wu, and G. Augenbroe (2015). Quantification of model form uncertainty in the calculation of solar diffuse irradiation on inclined surfaces for building energy simulation. Journal of Building Performance Simulation, 8, 253-265.
163. Dianpeng Wang, Y. Tian, and C. F. J. Wu (2015). A skewed version of the Robbins-Monro-Joseph procedure
for binary response. Statistica Sinica, 25, 1679-1689.
164. Rui Tuo and C. F. J. Wu (2015). Efficient calibration for imperfect computer models. Ann. Stat., 43, 2331-
2352.
165. 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.
166. Yijie D. Wang and C. F. J. Wu (2017). Bayesian cubic spline in computer experiments. In “Handbook of Uncertainty Quantification” (Eds. R. Ghanem, D. Higdon, and H. Owhadi), Volume 1, 477-495, CRC Press.
167. Su, Heng and C. F. J. Wu (2017). CME Analysis: a new method for unraveling aliased effects in two-level fractional factorial experiments. J. Quality Technology, 49, 1-10. (winner of the Brumbaugh Award).
168. X. He, Rui Tuo and C. F. J. Wu (2017). Optimization of multi-fidelity computer experiments via the EQIE criterion. Technometrics, 59, 58-68.
169. R. B. Chen, W. Wang and C. F. J. Wu (2017). Sequential designs based on Bayesian uncertainty quantification in
sparse representation surrogate modeling. Technometrics, 59, 139-152.
170. Heng Su and C. F. Jeff Wu (2017). Funnel testing in webpage optimization: representation, design and analysis.
Statistical Theory and Related Fields (Taylor Francis), 1, 3-14.
171. R. Mukerjee, C. F. J. Wu and M. C. Chang (2017). Two-level minimum aberration designs under a conditional model with a pair of conditional and conditioned factors. Statistica Sinica, 27, 997-1016.
172. Rui Tuo and C. F. J. Wu (2018). Prediction based on the Kennedy-O’Hagan calibration model:
asymptotic consistency and other properties. Statistica Sinica, 28, 743-759.
173. C. F. Jeff Wu (2018). A fresh look at effect aliasing and interactions: some new wine in old bottles (with
discussions), Ann. Inst. Stat. Math. 70, 249–268 (written version of the 2016 Akaike Memorial Lecture.)
174. 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.
175. S. T. Yeh, X. J. Wang, C. L. Sung, S. Mak, Y. H. Chang, C. F. J. Wu and V. Yang (2018). Data-driven
analysis and mean flow prediction using a physics-based surrogate model for design exploration. AIAA Journal,
56(6): 2429-2442.
176. 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.
177. H. Su, Rui Tuo, and C. F. J. Wu (2019). PIG Process: joint modeling of point and integral responses in
computer experiments. International J. for Uncertainty Quantification, 9, 331–349.
178. Simon Mak and C. F. J. Wu (2019). Analysis-of-marginal-Tail-Means: a new method for robust
parameter optimization. Technometrics, 61, 545-559.
179. Chang, Y.-H., Zhang, L., Yeh, S.-T., Wang, X. J., Mak, S., Sung, C.-L., Wu, C. F. J. and Yang, V. (2019). Kernel-
smoothed proper orthogonal decomposition-based emulation for prediction of spatiotemporally evolving flow
dynamics. AIAA Journal, 57(12): 5269-5280.
180. Dianpeng Wang, Y. Tian, and C. F. J. Wu (2020). Comprehensive comparisons of major sequential design
procedures for sensitivity testing. J. Quality Technology, 52, 155-167.
181. C. L. Sung, Y. Hung, W. Rittase, C. Zhu and C. F. J. Wu (2020). A generalized Gaussian process model for computer experiments with binary time series. Journal of American Statistical Association, 115, 945-956.
182. Wenjia Wang, Rui Tuo and C. F. J. Wu (2020). On the prediction properties of kriging: uniform error bounds
and robustness. Journal of American Statistical Association, 115, 920-930.
183. R. B. Chen, Yuan Wang and C. F. J. Wu (2020). Global optimization of expensive functions using adaptive
RBF-based surrogate model via uncertainty quantification. J. Global Optimization, 77, 919–948
184. C. L. Sung, Y. Hung, W. Rittase, C. Zhu and C. F. J. Wu (2020). Calibration for computer experiments with
binary responses. Journal of American Statistical Association, 115, 1664-1674.
185. Rui Tuo, Yan Wang and C. F. J. Wu (2020). On the improved rates of convergence for Matern-type
kernel ridge regression, with application to calibration of computer models. SIAM/ASA Journal on Uncertainty
Quantification, 8, 1522-1547.
186. Y. H. Chang, X. J. Wang, L. Zhang, Y. Li, S. Mak, C. F. J. Wu and V. Yang (2021).
Common kernel-smoothed proper orthogonal decomposition (CKSPOD): an efficient reduced-order model for
emulation of spatiotemporally evolving flow dynamics. AIAA Journal, 59(9): 3291-3303.
187. Y. Hung, L. H. Lin and C. F. J. Wu (2022). Varying coefficient frailty models with applications in
single molecular experiments. Biometrics, 78, 474-486.
188. S. Xiong, C. Li, X. Sun, Y. Qin, and C. F. Jeff Wu (2022). Statistical estimation in passenger-to-train
assignment models based on automated data. Appl. Stochastic Models Bus. Ind., 38, 287-307.
189. Jialei Chen, Zhehui Chen, Chuck Zhang and C. F. J. Wu (2022). APIK: Active Physics-Informed Kriging Model
with Partial Differential Equations. SIAM/ASA Journal on Uncertainty Quantification, 10, 481-506.
190. Wenjia Wang, X. Yue, B. Haaland, and C. F. J. Wu (2022). Gaussian process with input location error
and applications to the composite parts assembly process. SIAM/ASA Journal on Uncertainty
Quantification, 10, 619-650.
191. Simon Mak, Yuanshuo Zhao, Lavonne Hoang, C. F. J. Wu (2022). TSEC: a framework for online experimentation
under experimental constraints. Technometrics, 64(4), 513-523.
192. Y. Hung, L. H. Lin and C. F. J. Wu (2023). Optimal simulator selection. Journal of American Statistical Association,
118, 1264-1271.
193. H. S. Yuchi, V. R. Joseph, and C. F. J. Wu (2023). Design and Analysis of Finite Element Simulations. J.
of Mechanical Design, 145(6), 061703.
194. 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.
195. Y. Ji, H. S. Yuchi, D. Soeder, J.-F. Paquet, S. A. Bass, V. R. Joseph, C. F. J. Wu, Simon Mak (2024).
Conglomerate multi-fidelity Gaussian process modeling, with application to Heavy-Ion collisions. SIAM/ASA
Journal on Uncertainty Quantification, 12(2), 473-502.
196. Zhaohui Li, Shihao Yang and C. F. J. Wu (2024). Parameter Inference based on Gaussian Processes Informed by
Nonlinear Partial Differential Equations. SIAM/ASA Journal on Uncertainty Quantification, 12(3), 964-1004.