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Daniel W. Apley Editor-in-Chief-Elect,
Technometrics Dept. of Industrial Engineering and
Management Sciences McCormick
School of Engineering and Applied Science 2145 Sheridan Road Evanston IL 60208-3119 office: Technological Institute
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Research and Teaching Overview I am a Professor of Industrial Engineering and Management Sciences at
Northwestern University, Evanston, IL. I obtained B.S., M.S., and Ph.D. degrees
in Mechanical Engineering and an M.S. degree in Electrical Engineering from
the University of Michigan. Prior to joining Northwestern University in 2003,
I served on the faculty of Texas A&M University for five years. I am an
industrial statistician with research interests that lie at the interface of
engineering modeling, statistical analysis, and predictive analytics. My work
has been supported by numerous industries and government agencies, and I
received the NSF CAREER award, the IIE Transactions Best Paper Award, and the
Wilcoxon Prize for best practical application paper appearing in Technometrics. I currently serve as Editor-in-Chief Elect for Technometrics, the premier journal of the
American Statistical Association and the American Society for Quality on
statistical methods for the engineering, physical, chemical, and information
sciences. I have also served as Editor-in-Chief for the Journal
of Quality Technology, Chair of the Quality, Statistics &
Reliability Section of INFORMS, and Director of the Manufacturing and Design
Engineering Program at Northwestern. RESEARCH AND TEACHING OVERVIEW My broad areas of research and teaching interest are: · Industrial/engineering statistics · Statistical learning, data mining, and predictive analytics · Statistical quality control and six sigma variation reduction · Manufacturing process diagnosis and automatic control I am an industrial statistician with research interests that lie at the interface of engineering modeling, statistical analysis, and predictive analytics, especially with large and complex data structures. Much of my work addresses the problem of how to transform large amounts of data into useful information. One important application domain involves developing quantitative six sigma process improvement tools that are suitable for modern manufacturing and design processes inundated with high-dimensional, high-volume data from automated measurement, data collection, and process control technologies, coupled with CAD/CAM and computer simulation data. Some of my research in this area develops statistical methodologies for discovering and visualizing pieces of information buried in large databases that will help engineers systematically identify and eliminate root causes of product and process variation. Another body of my research in this area develops methodologies for designing and analyzing computer simulation experiments, sometimes coupled with data from physical experiments. I also conduct research solving data-intensive problems in other application domains that include business intelligence, healthcare engineering, product/process design optimization, and financial risk assessment. Recent projects in these areas include developing predictive models for strategic management of credit risk based on large-scale customer databases; Bayesian statistical analyses for product and process design optimization based on finite element computer simulations; reliable assessment of disease risk factors from error-prone electronic medical records; and statistical modeling of microstructure behavior for predictive materials science. At Northwestern, I teach undergraduate courses in Statistical Methods for Quality Improvement (IEMS 305), Introductory Statistics (IEMS 303), and Statistical Tools for Data Mining (IEMS 304). I also teach graduate courses in Predictive Analytics (MSiA 420), Engineering Applications of Data Mining (IEMS 490), and Intermediate Statistics (IEMS 401). McElroy, L. M.,
Khorzad, R., Rowe, T. A., Abecassis, Z. A., Apley, D. W., Barnard, C., and
Holl, J. L., "Fault Tree Analysis: Assessing the Adequacy of Reporting
Efforts to reduce Postoperative Bloodstream infection," American
Journal of Medical Quality, to appear. Li, W., Chen, S.,
Jiang, Z, Apley, D. W., Lu, Z., Chen, W., "Integrating Bayesian
Calibration, Bias Correction, and Machine Learning for the Validation
Challenge Problem," ASME Journal of Verification, Validation and
Uncertainty Quantification, to appear. Bostanabad, R., Bui*, A. T.,
Xie, W., Apley, D. W., and Chen, W., "Stochastic
Microstructure Characterization and Reconstruction via Supervised Learning,"
Acta Materialia,
doi:10.1016/j.actamat.2015.09.044, 103, pp. 89102. Xu, H., Jiang, Z.,
Apley, D. W., and Chen, W., "New Metrics for the Validation of
Data-Driven Random Process Models in Uncertainty Quantification," ASME
Journal of Verification, Validation and Uncertainty Quantification, DOI:
10.1115/1.4031813, 1(1), pp. 011002-1011002-14. Chen, S. Jiang, Z.,
Yang, S., Apley, D. W., and Chen, W., "Nonhierarchical
Multi-model Fusion Using Spatial Random Processes," International
Journal for Numerical Methods in Engineering, to appear. Ouyang, L., Apley,
D. W., and Mehrotra, S., "A
Design of Experiments Approach to Validation Sampling for Logistic Regression
Modeling with Error-Prone Medical Records," Journal of the
American Medical Informatics Association, to appear, DOI: 10.1093/jamia/ocv132. Zhang, N. and Apley,
D. W., "Brownian
Integrated Covariance Functions for Gaussian Process Modeling: Sigmoidal Versus Localized Basis Functions,"
Journal of the American Statistical Association, to appear,
DOI:10.1080/01621459.2015.1077711. Arendt, P., Apley,
D. W., and Chen, W., "A Preposterior Analysis to Predict Identifiability in
Experimental Calibration of Computer Models," IIE Transactions,
to appear, DOI: 10.1080/0740817X.2015.1064554. with supplement. Jiang, Z., Li, W.,
Apley, D. W., and Chen, W., "A
Spatial-Random-Process Based Multidisciplinary System Uncertainty Propagation
Approach with Model Uncertainty," ASME Journal of Mechanical
Design, 137(10), pp. 101402, 2015. Jiang, Z., Apley,
D. W., and Chen, W., "Surrogate Preposterior Analyses for Predicting and Enhancing
Identifiability in Model Calibration," International Journal for
Uncertainty Quantification, DOI:
10.1615/Int.J.UncertaintyQuantification.2015012627, 5(4), pp. 341359, 2015. Shi, Z., Apley, D.
W., and Runger, G. C., "Discovering the Nature
of Variation in Nonlinear Profile Data," Technometrics,
to appear. with supplement. Gramacy, R. B. and
Apley, D. W., Local
Gaussian process approximation for large computer experiments, Journal
of Computational and Graphical Statistics,
DOI:10.1080/10618600.2014.914442, 24(2), pp. 561578, 2015. draft version. Sahu, A., Apley, D. W.
and Runger, G., "Feature selection for noisy
variation patterns using kernel principal component analysis, Knowledge-Based
Systems, DOI: 10.1016/j.knosys.2014.08.027, 72, pp. 3747, 2014. Zhang, N. and
Apley, D. W., "Fractional
Brownian Fields for Response Surface Metamodeling," Journal of
Quality Technology, 46(4), pp. 285301, 2014. Shinde, A., Sahu, A., Apley, D., and Runger,
G., "Preimages
for Variation Patterns from Kernel PCA and Bagging," IIE
Transactions, 46(5), pp. 429456, 2014. Arendt, P. D.,
Apley, D. W., and Chen, W., "Objective
- Oriented Sequential Sampling for Simulation Based Robust Design Considering
Multiple Sources of Uncertainty," ASME Journal of Mechanical
Design, 135(5), doi: 10.1115/1.4023922, 2013. Arendt, P. D.,
Apley, D. W., and Chen, W., "Quantification
of Model Uncertainty: Calibration,
Model Discrepancy, and Identifiability," ASME Journal of
Mechanical Design, 134(10), 100908-1100908-12, doi:10.1115/1.4007390, 2012. Arendt, P. D.,
Apley, D. W., Chen, W., Lamb, D. and Gorsich, D.,
"Improving
Identifiability in Model Calibration Using Multiple Responses," ASME
Journal of Mechanical Design, 134(10), 100909-1100909-9,
doi:10.1115/1.4007573, 2012. Apley, D. W.,
"Posterior
Distribution Charts: A Bayesian
Approach for Graphically Exploring a Process Mean," Technometrics, 54(03), pp. 296 310, 2012 Im, J. K., Apley,
D. W., and Runger, G., "Tangent
Hyperplane Kernel Principal Component Analysis for Denoising,"
IEEE Transactions on Neural Networks, 23(4), pp. 644656, April, 2012. Im, J. K., Apley,
D. W., Shan, X., and Qi, C., "A
Time Dependent Proportional Hazards Survival Model for Credit Risk Analysis,"
Journal of the Operational Research Society, 63(3), pp. 306321, March,
2012. Sun, Y. Apley, D.
W., and Staum, J., "Efficient Nested
Simulation for Estimating the Variance of a Conditional Expectation,"
Operations Research, 59(4), pp. 9981007, JulyAugust 2011 Apley, D. W. and
Kim, J. B., "A
Cautious Approach to Robust Parameter Design with Model Uncertainty,"
IIE Transactions, 43(7), pp. 471-482, 2011. Lee, H. C. and
Apley, D. W., "Improved
Design of Robust Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes," Quality and
Reliability Engineering International, 27(3), pp. 337-352, 2011. Apley, D. W. and
Lee, H. C., "The
Effects of Model Parameter Deviations on the Variance of a Linearly Filtered
Time Series," Naval Research Logistics, 57(5), pp. 460-471,
August, 2010. Apley, D. W.,
"Discussion
of Nonparametric Profile Monitoring by Mixed Effects Modeling," Technometrics, 52(3), pp. 277-280, August, 2010. Apley, D. W. and
Lee, H. Y., "Simultaneous
Identification of Premodeled and Unmodeled Variation Patterns," Journal of
Quality Technology, 42(1), pp. 3651, January, 2010. Xiong, Y., Chen, W., Tsui, K. L., and Apley, D. W., "A
Better Understanding of Model Updating Strategies in Validating Engineering
Models," Computer Methods in Applied Mechanics and Engineering,
198, pp. 13271337, March, 2009. Apley, D. W. and
Lee, H. C., "Robustness
Comparison of Exponentially Weighted Moving Average Charts on Autocorrelated Data and on Residuals," Journal
of Quality Technology, 40(4), pp. 428-447, October, 2008. Jiang, W., Shu, L.,
and Apley, D. W. "Adaptive
CUSUM Procedures with EWMA-based Shift Estimators," IIE
Transactions, 40(10), pp. 992-1003, October, 2008. Shan, X. and Apley,
D. W., "Blind
Identification of Manufacturing Variation Patterns by Combining Source
Separation Criteria," Technometrics,
50(3), pp. 332343, August, 2008. Chin, C. H. and
Apley, D. W., "Performance
and Robustness of Control Charting Methods for Autocorrelated
Data," Journal of the Korean Institute of Industrial Engineers,
34(2), pp. 122139, June, 2008. Ding, Y. and Apley,
D. W., "Guidelines
for Placing Additional Sensors to Improve Variation Diagnosis in Assembly
Processes," International Journal of Production Research,
45(23), pp. 5485-5507, December, 2007. Xiong, Y., Chen, W.,
Apley, D. W., and Ding, X. "A
Nonstationary Covariance Based Kriging Method for Metamodeling in Engineering
Design," International Journal for Numerical Methods in
Engineering, 71(6), pp. 733-756, August, 2007. Apley, D. W., and
Zhang, F., "Identifying
and Visualizing Nonlinear Variation Patterns in Multivariate Manufacturing
Data", IIE Transactions, 39(6), pp. 691-701, June,
2007. Apley, D. W. and
Chin, C. H., "An
Optimal Filter Design Approach to Statistical Process Control," Journal
of Quality Technology, 39(2), pp. 93-117, April, 2007. Chin, C. H. and
Apley, D. W. "Optimal
Design of Second-Order Linear Filters for Control Charting," Technometrics, 48(3), pp. 337-348, August, 2006. Apley, D. W., Liu,
J. and Chen, W. "Understanding
the Effects of Model Uncertainty in Robust Design With Computer Experiments,"
ASME Journal of Mechanical Design, 128(4), pp. 945-958, July, 2006. Apley, D. W. and
Ding, Y., "A
Characterization of Diagnosability Conditions for
Variance Components Analysis in Assembly Operations," IEEE
Transactions on Automation Science and Engineering, 2(2), pp. 101-110,
April, 2005. Lee, H. Y. and
Apley, D. W. "Diagnosing
Manufacturing Variation Using Second-Order and Fourth-Order Statistics,"
International Journal of Flexible Manufacturing Systems, 16, pp.
45-64, 2004. Apley, D. W. and
Kim, J.B., "Cautious
Control of Industrial Process Variability with Uncertain Input and
Disturbance Model Parameters," Technometrics,
46(2), pp. 188-199, 2004. Ding, Y., Gupta, A.,
and Apley, D. W., "Singularity
Issues in Fixture Fault Diagnosis for Multi-Station Assembly Processes,"
ASME Journal of Manufacturing Science and Engineering, 126(1), pp.
200-210, 2004. Apley, D. W.,
"A
Cautious Minimum Variance Controller with ARIMA Disturbances," IIE
Transactions, 36(5), pp. 417-432, 2004. Shiu, B. W., Apley, D.
W., Ceglarek, D., and Shi, J., "Tolerance
Allocation for Compliant Beam Structure Assemblies," IIE
Transactions, 35(4), pp. 329-342, 2003. Apley, D. W. and
Lee, H. Y., "Identifying
Spatial Variation Patterns in Multivariate Manufacturing Processes: A Blind Separation Approach," Technometrics, 45(3), pp. 220-234, 2003. Apley, D. W. and
Lee, H. C., "Design
of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes with Model Uncertainty,"
Technometrics, 45(3), pp. 187-198, 2003. Tsung, F. and
Apley, D. W., "The
Dynamic T2 Chart for Monitoring Feedback-Controlled
Processes," IIE Transactions, 34(12), pp. 1043-1053,
2002. Received the 2002-2003 IIE Transactions Best Paper
Award for Quality and Reliability. Apley, D. W.,
"Time
Series Control Charts in the Presence of Model Uncertainty," ASME
Journal of Manufacturing Science and Engineering, 124(4), pp. 891-898,
2002. Shu, L., Apley,
D.W., and Tsung, F. "Autocorrelated
Process Monitoring Using Triggered Cuscore Charts," Quality
and Reliability Engineering International, 18(5), pp. 411-421, 2002. Apley, D. W. and
Tsung, F., "The
Autoregressive T2 Chart for Monitoring
Univariate Autocorrelated Processes," Journal
of Quality Technology, 34(1), pp. 80-96, 2002. Apley, D. W. and
Shi, J., "A
Factor Analysis Method for Diagnosing Variability in Multivariate
Manufacturing Processes," Technometrics,
43(1), pp. 84-95, 2001. Apley, D. W. and
Shi, J., "The
GLRT for Statistical Process Control of Autocorrelated
Processes," IIE Transactions, 31(12), pp. 1123-1134, 1999. Apley, D. W. and
Shi, J., "An
Order Downdating Algorithm for Tracking System
Order and Parameters in Recursive Least Squares Identification," IEEE
Transactions on Signal Processing, 47(11), pp. 3134-3137, 1999. Apley, D. W. and
Shi, J., "Diagnosis
of Multiple Fixture Faults in Panel Assembly," ASME Journal of
Manufacturing Science and Engineering, 120(4), pp. 793-801, 1998. Shi, J. and Apley,
D. W., "A
Suboptimal N-step-ahead Cautious Controller for Adaptive Control Applications,"
ASME Journal of Dynamic Systems, Measurement, and Control, 120(3), pp.
419-423, 1998. Apley, D. W., Seliger, G., Voit, L., and Shi,
J., "Diagnostics
in Disassembly Unscrewing Operations," International Journal of
Flexible Manufacturing Systems, 10(2), pp. 111-128, 1998. |