I earned my PhD in Statistics and Operations Research from The Pennsylvania State University in 2010, with advisors Enrique del Castillo and James Rosenberger. I study the design and analysis of experiments, particularly practical and algorithmic approaches to screening and model-robust designs, as well as regularization methods for their analysis. Much of my work involves applied optimization, and I also have an interest in statistical consulting and collaboration, in areas including experimental design and predictive modeling. More recently, in addition to research in experimental design, I have worked on issues of experimental design pedagogy, statistical engineering, and subsampling in big data settings.
For a curated list of papers, see my CV (updated 11/15/2023).
Submitted / In Revision / In Process
Cui, M., Qi, K., Smucker, B., and Sundaramoorthi, D. A Multi-Objective Capacity-Constrained Optimization of Corn Planting Scheduling. Submitted. [pdf]
Tsissios, G., Sallese, A., Perez-Estrada, J.R., Tangeman, J.A., Chen, W., Smucker, B., Ratvasky, S.C., Grajales-Esquivel, E., Martinez, A., Visser, K.J., Araus, A.J., Wang, H., Simon, A., Yun, M.H., Del Rio-Tsonis, K. Macrophages modulate fibrosis during newt lens regeneration. Submitted. [bioRxiv preprint]
Perez-Estrada, J.R., Tangeman, J., Proto-Newton, M., Sanaka, H., Smucker, B., and Del Rio-Tsonis, K. Distinct Metabolic States Direct Retinal Pigment Epithelium Cell Fate Decisions. In revision. [bioRxiv preprint]
Stallrich, J.W., Young, K., Weese, M.L., Smucker, B.J., and Edwards, D.J. Optimal Supersaturated Designs for Lasso Sign Recovery. [arXiv preprint]
Tsissios, G., Theodoroudis-Rapp, G., Chen, W., Sallese, A., Smucker, B., Ernst, L., Chen, J., Xu, Y., Ratvasky, S., Wang, H., and Del Rio-Tsonis, K. (2023). Characterizing the lens regeneration process in Pleurodeles waltl. Differentiation, 132:15-23. [bioRxiv preprint].
Smucker, B.J., Stevens, N.T., Asscher, J., and Goos, P. (2023). Profiles in the Teaching of Experimental Design and Analysis. Journal of Statistics and Data Science Education, DOI: 10.1080/26939169.2023.2205907. [pdf] [Supplemental Material]
Tangeman, J.A., Perez-Estrada, J.R., Van Zeeland, E., Liu, L., Danciutiu, A., Grajales-Esquivel, E., Smucker, B., Lian, C., and Del Rio-Tsonis, K. (2022). A stage-specific OTX2 regulatory network and maturation-associated gene programs are inherent barriers to RPE neural competency. Frontiers in Cell and Developmental Biology, section Molecular and Cellular Pathology, 10.3389/fcell.2022.875155.
Zhang, J., Kong, Y., Bailer, A.J., Zhu, Z., and Smucker, B.J. (2022). Incorporating Historical Data when Determining Sample Size Requirements for Aquatic Toxicity Experiments. Journal of Agricultural, Biological, and Environmental Statistics, 27:544-561.
Snyder, M. and Smucker, B.J. (2022). Metamodel Optimization of a Complex, Rural-Urban Emergency Medical Services System. Simulation Modelling Practice and Theory, 148, 10.1016/j.simpat.2022.102526.
[pdf] [Supplemental Material] Embargoed until March 2024.
Weese, M.L., Stallrich, J.W., Smucker, B.J., and Edwards, D.J. (2021). Strategies for Supersaturated Screening: Group Orthogonal and Var(s+) Designs. Technometrics, 63:4, 443-455, DOI: 10.1080/00401706.2020.1850529. [pdf] [Supplemental Material]
Chen, W., Tsissios, G., Sallese, A., Smucker, B., Nguyen, A.-T., Chen, J., Wang, H., and Del Rio-Tsonis, K. (2021). In vivo imaging of newt lens regeneration: Novel insights into the regeneration process. Translation Vision Science & Technology, 10:10. [pdf]
Smucker, B.J., Edwards, D.J., and Weese, M.L. (2021). Response Surface Models: To Reduce or Not to Reduce?. Journal of Quality Technology, 53:2, 197-216. [pdf] [Supplemental Material]
Liu, C. and Smucker, B.J. (2020). Leveraging Methods for Subsampling: Towards a Realistic Evaluation. Peer-reviewed presentation at Symposium on Statistics & Data Science (peer-reviewed extended abstract), Pittsburgh, June 3-6. [pdf]
Smucker, B., Krzywinski, M., and Altman, N. (2019). Points of Significance: Two-level factorial experiments (invited column). Nature methods, 16:211-212.
Smucker, B., Krzywinski, M., and Altman, N. (2018). Points of Significance: Optimal experimental design (invited column). Nature methods, 15(8):559-560.
Yousefi, A.M., Smucker, B.J., Naber, A.J., Wyrick, C.S., Shaw, C.H., Bennett, K., Szekely, S.E., and Focke, C.A. (2018). Controlling the extrudate swell in melt extrusion additive manufacturing of 3D scaffolds: a designed experiment. Journal of Biomaterials Science, Polymer Edition, 29(3):195-216.
Weese, M.L., Edwards, D.J., and Smucker, B.J. (2017). A Criterion for Constructing Powerful Supersaturated Designs when Effect Directions are Known. Journal of Quality Technology, 49(3):265-277. [pdf] [Supplementary Material]
Smucker, B.J., Jensen, W., Wu, Z., and Wang, B. (2017). Robustness of Classical and Optimal Designs to Missing Observations. Computational Statistics & Data Analysis, 113:251-260. [pdf] [Designs]
Ockuly, R., Weese, M.L., Smucker, B.J., Edwards, D.J, and Chang, L. (2017). Response Surface Experiments: A Meta-Analysis. Chemometrics and Intelligent Laboratory Systems. 164:64-75. [pdf] [Meta-Analysis Bibliography] [Meta-Analysis Datasets]
Uth, N., Mueller, J., Smucker, B., and Yousefi, A.-M. (2017). Validation of Scaffold Design Optimization in Bone Tissue Engineering: Finite Element Modeling versus Designed Experiments. Biofabrication. 9(1). [pdf]
Cao, Y., Smucker, B.J., and Robinson, T.J. (2017). A Hybrid Elitist Pareto-based Coordinate Exchange Algorithm for Constructing Multi-Criterion Optimal Experimental Designs. Statistics & Computing, 27, 423-437. [pdf]
Smucker, B.J. and Bailer, A.J. (2015). Beyond Normal: Preparing Undergraduates for the Work Force in a Statistical Consulting Capstone. The American Statistician, 69(4):300-306. [pdf of original submission] [Supplementary Material]
Zhang, X., Smucker, B.J., and Woffington, J. (2015) Statistics and Show Business: Shakespeare Meets Predictive Analytics. Chance, 28.2:4-12. [html] [pdf] [shiny app] [simplified dataset] [Cincinnati Business Courier article]
Smucker, B.J. and Drew, N.M. (2015). Approximate Model Spaces for Model-Robust Experiment Design. Technometrics, 57(1):54-63. [pdf] [Supplementary Material]
Cao, Y., Smucker, B.J., and Robinson, T.J. (2015). On using the hypervolume indicator to compare Pareto fronts: Applications to multiple optimal experiment design. Journal of Statistical Planning & Inference, 160:60-74. [pdf] [Supplementary Material]
Yousefi, A.-M., Szekely, S., Shaw, C., Reichenbach, K., Naber, A., Janney, C., Focke, C., Smucker, B. (2015). Extrusion-based Additive Manufacturing: The Effect of Extrudate Swell. Proceedings of SPE-ANTEC Conference, Orlando, FL, March 23-25.
Keane, B., Parsons, S., Smucker, B.J., and Solomon, N.G. (2014). Length polymorphism at the avpr1a locus is correlated with male reproductive behavior in a natural population of prairie voles (Microtus ochrogaster). Behavioral Ecology and Sociobiology, 68(12):1951-1964. [pdf]
Webb, J., Smucker, B.J. and Bailer, A.J. (2014). Selecting the best design for nonstandard toxicology experiments. Environmental Toxicology and Chemistry, 33(10):2399-2406. [docx] [figures] [tables]
Wright, S.E. and Smucker, B.J. (2014). Rapid calculation of exact cell bounds for contingency tables from conditional frequencies. Computers and Operations Research. 52:113-122. [pdf]
Wright, S.E. and Smucker, B.J. (2013). An intuitive formulation and solution of the exact cell-bounding problem for contingency tables of conditional frequencies. Journal of Privacy and Confidentiality. 5(2):133-156. [pdf] [code]
Smucker, B.J. (2012). Discussion of ”Optimum design of experiments for statistical inference” by Gilmour and Trinca. Journal of the Royal Statistical Society: Series C (Applied Statistics). 61(3):345-401.
Smucker, B.J., del Castillo, E., and Rosenberger, J.L. (2012). Model-Robust Designs for Split Plot Experiments. Computational Statistics and Data Analysis, 56(12):4111-4121. [pdf] [Supplementary Material]
Smucker, B.J., del Castillo, E., and Rosenberger, J.L. (2012). Model-Robust Two-Level Designs Using Coordinate Exchange Algorithms and a Maximin Criterion. Technometrics, 54(4):367-375. [pdf] [Supplementary Material]
Smucker, B.J., Slavković, A., and Zhu, X. (2012). Cell Bounds in k-way Tables Given Conditional Frequencies. Journal of Official Statistics, 28(1):121-140.
Smucker, B.J., del Castillo, E., and Rosenberger, J.L. (2011). Exchange Algorithms for Constructing Model-Robust Experimental Designs. Journal of Quality Technology. 43(1):28-42. [pdf].
Smucker, B.J., Lorantas, R., and Rosenberger, J.L. (2010). Correcting Bias Introduced by Aerial Counts in Angler Effort Estimation. North American Journal of Fisheries Management, 30(4):1051-1061.
Smucker, B. and Slavković, A (2008). Cell bounds in two-way contingency tables based on conditional frequencies. In Domingo-Ferrer, J. and Saygin, Y., editors, Privacy in Statistical Databases 2008 Lecture Notes in Computer Science, volume 5262, pages 64-76. Springer-Verlag, Berlin Heidelberg.
Logendran, R., McDonell, B., and Smucker, B. (2007). Scheduling unrelated parallel machines with sequence-dependent setups. Computers and Operations Research, 34(11):3420-3438.
Smucker, B.J. (2010). By Design: Exchange Algorithms to Construct Exact Model-Robust and Multiresponse Experimental Designs. Ph.D. Dissertation, The Pennsylvania State University.
Smucker, B.J. (2007). Calculating Cell Bounds in Contingency Tables Based on Conditional Frequencies. Master’s Thesis, The Pennsylvania State University.
“Meta-Model Optimization of Simulated EMS Systems: A Case of Statistical Engineering.” World Statistics Conference (virtual). July 2021.
“A Positive View of Data Ethics.” Diversity and Inclusion Conference: Data Ethics and Algorithmic Bias, Miami University. September 2020. [Video (approximately 12:00-32:00)]
“Experimental design ideas in data science: an overview.” Joint Statistical Meetings (Virtual). August 2019.
“An Introduction to Split-Plot Experiments with Application to Bone Tissue Engineering.” Central Regional Meeting (CERM) of the American Chemical Society, Midland, MI. June 2019.
“Model-Robust Mixture Experiments.” Spring Research Conference, Blacksburg, VA. May 2019.
“Predictive Response Surface Models: To Reduce or Not to Reduce?.” Fall Technical Conference, West Palm Beach, FL. October 2018.
“Evaluating and Constructing Designs for Robustness to Unusable Observations.” IFPAC-2017, North Bethesda, MD. March 2017.
“A Meta Analysis of Response Surface Experiments.” Fall Technical Conference, Minneapolis. October 2016.
“Generating and Comparing Pareto Fronts of Experiment Designs to Simultaneously Account for Multiple Experimental Objectives.” DEMA2015, Sydney, Australia. December 2015.
“Approximate Model Spaces for Model-Robust Experiment Design.” Department of Statistics and Operations Research, Virginia Commonwealth University. March 2014.
“Candidate-List-Free Exchange Algorithms for Two-Level Model-Robust Designs.” Fall Technical Conference, Kansas City. Contributed. October 2011.
“Correcting Bias Introduced by Aerial Counts in Angler Effort Estimation.” American Fisheries Society Annual Meeting, Pittsburgh. September 2010.
“Exchange Algorithms for Model-Robust, Exact Experimental Designs.” Miami University at Oxford, OH. March 2010.
“Cell bounds in two-way contingency tables based on conditional frequencies.” Privacy and Statistical Databases, Istanbul. Contributed. September 2008.