Enrique Del Castillo

Distinguished Professor of Industrial & Manufacturing Engineering; Professor of Statistics
Enrique Del Castillo
Enrique
Del Castillo
Distinguished Professor of Industrial & Manufacturing Engineering; Professor of Statistics
External Affiliations
Interests
Process Optimization
Experimental Design
Time Series Analysis & Control
Bayesian Statistics
Statistical Learning Theory
Manifold Learning
Address
Phone
(814) 863-6408
Website
Personal Site

Biography

Enrique del Castillo is a Distinguished Professor of Engineering at Penn State, and a professor in the Industrial and Manufacturing Engineering Department and in the Department of Statistics.

Castillo holds a B.S. in Mechanical and Electrical Engineering from the National University of Mexico/U. Panamericana in 1986, a Master of Engineering in Operations Research from Cornell University in 1988, and received his Ph.D. in Industrial Engineering (Statistics concentration) from Arizona State in 1992.

His research centers on “Engineering Statistics”, in particular, process and product quality control and optimization methods in industry, areas related to Time Series Analysis and Control, Design of Experiments, Response Surface Methodology, and Reliability Engineering. Due to the wide availability of sensors and the consequently increasing datasets, his work in control and optimization has evolved over the last decade to deal with problems involving not only larger but more complex datasets, such as large geometrical (or geometrical-spatial) datasets, specifically, functional, shape, surface and volumetric data (i.e., data that occurs in 1D or 2D-manifolds) as well as point cloud and image data, in work at the intersection of Statistical methodology, Engineering metrology and Machine Learning methods. His interests in on-line process optimization has resulted in recent work in the area of Active Learning with engineering applications. In addition to working in data-based engineering problems, Castillo has maintained secondary collaborations with scientists working in biology, evolutionary theory, and nutrition.

He is the author of over 120 refereed papers and the author of 2 textbooks: Statistical Process Adjustment for Quality Control (John Wiley & Sons, 2002) and Process Optimization: a Statistical Approach (Springer, 2007). He has served as editor in chief of the Journal of Quality Technology (2006-2009), where he currently serves in the editorial board, Associate Editor of Technometrics, and Associate Editor of the Institute of Industrial Engineers Transactions, in addition to serving as referee to over 20 journals in Statistics, Operations Research and Industrial Engineering. He is a member of ASA, RSS and INFORMS.

 

Honors and Awards

Castillo was a Fulbright Scholar in 2019 and 2006, and received an NSF CAREER grant in 1996-1999. His research has been funded by NSF, General Motors, Intel Corp., Netflix, Minitab, and NATO. He has held Visiting Professorships at Politecnico di Milano, Italy, the National University of Singapore, , Würzburg University, Germany, Tilburg University, Netherlands, Coimbra University, Portugal, and University of Navarra, Spain. Before coming to PSU in 1998, he held prior appointments at the University of Texas and at Centro de Investigacion en Matematicas (CIMAT), Mexico.

 

Publications

  • Zhao, X., and Del Castillo, E., “An Intrinsic Geometrical approach for Statistical Process Control of Surface and Manifold Data”, accepted in Technometrics, (2020).
     
  • Zhang, L., del Castillo, E., Berlung, A., Tingley, M., Govind, N., “Computing confidence intervals from massive data via penalized quantile smoothing splines”, Computational Statistics and Data Analysis, 144 (April), (2020).
     
  • House, C., Tunstall, P, Rapkin, J., Janicot, M., Gage, M., del Castillo, E., and Hunt, J., “Multivariate stabilizing sexual selection and the evolution of male and female genital morphology in the red flour beetle”, Evolution, 74(5), pp. 883-896, (2020).
     
  • Zhao, X., Pan, R., del Castillo, E., and Xie, M., “A Two-Stage Bayesian Model Averaging Approach to Planning and Analyzing Accelerated Life Tests Under Model Uncertainty”, J. of Quality Technology, 51(2), pp. 181-197 (2019).
     
  • Tajbakhsh, S., Aybat, S., and Del Castillo, E., “Generalized Sparse Precision Matrix Selection for Fitting Multivariate Gaussian Random Fields to Large Data Sets”, Statistica Sinica, 28, pp. 941-962 (2018).
     
  • Kee, S., E. del Castillo, G. Runger, “Query-by-committee improvement with diversity and density in batch active learning”, Information Sciences, 454-455, pp. 401-418, (2018).
     
  • Rapkin, J., Archer, R., House, C.M., Skaluk, S.K., del Castillo, E., and Hunt, J., “The geometry of nutritionally based life-history trade-offs: sex differences in the effect of macronutrient intake on the trade-off between immune function and reproductive effort in decorated crickets”, The American Naturalist, Vol. 191 (no. 4), pp. 452-474, (2018).
     
  • Del Castillo, E., Colosimo, B., and Tajbakhsh, S. “Geodesic Gaussian Processes for the Reconstruction of a 3D Free-Form Surface”, Technometrics, 57:1, pp. 87-99, (2015).
     
  • Smucker, B., Del Castillo, E., and Rosenberger, J., ”Model-Robust Two-Level Designs Using Coor- dinate Exchange Algorithms and a Maximin Criterion”, Technometrics, 54(4), pp. 367-375, (2012).
     
  • Del Castillo, E., and Colosimo, B.M., “Statistical Shape Analysis of Experiments for Manufacturing Processes”, Technometrics, 53(1), pp. 1-15, (2011).

 

Teaching

  • IE 433 Regression and Design of Experiments
     
  • IE 511 Design of Engineering Experiments
     
  • IE 532 Reliability Engineering
     
  • IE 583 Response Surface Methods and Process Optimization
     
  • IE 584 Time Series and Process Control