Click on a presentation title to see its abstract. At-a-Glance Schedule – Wednesday, October 9 8:00a – 9:00a Welcome & Plenary Session Gerald J. Hahn Achievement Award Experimental Mathematics—Friend or Foe? Fred Faltin, Virginia Tech Moderator: Jon Stallrich TBD TBD TBD 9:15a – 10:00a 1A: AI, BI & SI—Artificial Intelligence, Biological Intelligence and Statistical Intelligence Dennis Lin, Purdue University Moderator: Caleb King 1B: Quality by Design for the Era of Precision Medicine Julia O’Neill, Direxa Consulting LLC Moderator: Amanda Yoder 1C: Calibration and Uncertainty Quantification for Estimating Topographic Speedup Factors with CFD Models Adam Pintar, NIST Moderator: Di Michelson 10:30a – 12:00p 2A: Robust Experimental Designs Minimally aliased D- and A-optimal Main-effects Designs Mohammed Saif Ismail Hameed, KU Leuven Optimal Designs Under Model Uncertainty Xietao Zhou, King’s College London Moderator: Fred Faltin 2B: Model Estimation Peelle’s Pertinent Puzzle and D’Agostini Bias — Estimating the Mean with Relative Systematic Uncertainty Scott Vander Wiel, LANL Estimation and Variable Selection of Conditional Main Effects for Generalized Linear Models Kexin Xie, Virginia Tech Moderator: Yeng Saanchi 2C: Technometrics Invited Session Drift vs Shift: Decoupling Trends and Changepoint Analysis Toryn Schafer, Texas A&M Building Trees for Probabilistic Prediction via Scoring Rules Sara Shashaani, NC State Moderator: Bobby Gramacy 12:15a-1:45p Luncheon Reflections on a Career at Eastman in Statistics Kevin White, Eastman Moderator: Stephanie DeHart 2:00p – 3:30p 3A: STAT Invited Session XGBoost Modeling for Live Use in Manufacturing Amanda Yoder, Corning Can You Dig It? Using Machine Learning to Efficiently Audit Utility Locator Tickets Prior to Excavation to Protect Underground Utilities Jennifer H. Van Mullekom, Virginia Tech Moderator: Karen Hulting 3B: Deep GPs Deep Gaussian Processes for Surrogate Modeling with Categorical Data Andrew Cooper, Virginia Tech Generating Higher Resolution Sky Maps Using a Deep Gaussian Process Poisson Model Steven D. Barnett, Virginia Tech Moderator: Ayumi Mutoh 3C: DOE Selection of Initial Points Using Latin Hypercube Sampling for Active Learning Roelof Coetzer, North-west University Optimal Experimental Designs for Process Robustness Studies Peter Goos, KU Leuven Moderator: Steven Gilmour 4:00p – 5:00p W. J. Youden Address Youden’s Enduring Legacy at NIST Adam Pintar, NIST Moderator: Steve Schuelka At-a-Glance Schedule – Thursday, October 10 TBD TBD TBD 8:00a – 9:30a 4A: CPID Invited Session On the Testing of Statistical Software Ryan Lekivetz, JMP BayesFLo: Bayesian Fault Localization of Complex Software Systems Irene Ji, Duke Moderator: Jennifer Kensler 4B: SPC On Forming Control Limits for Short Run Standardized Xbar Control Charts with Varying Subgroup Sizes Annie Dudley and Di Michelson, JMP and Bill Woodall, Virginia Tech A Novel Robust MCUSUM for Phase II Profile Monitoring Abdel-Salam G. Abdel-Salam, Qatar University Moderator: Shane Bookholtz 4C: JQT Invited Session Nonparametric Online Monitoring of Dynamic Networks Peihua Qiu, University of Florida A Graphical Comparison of Screening Designs using Support Recovery Probabilities Kade Young, Eli Lilly & Co. Moderator: Fadel Megahed 10:00a – 11:30a 5A: SPES Invited Session Machine Learning, Cross Validation, and DOE Maria Weese, Miami University Autonomy versus Safety: Joint Modeling of Disengagement and Collision Events in Autonomous Vehicle Driving Study Simin Zheng, Virginia Tech Moderator: Michael Crotty 5B: Screening Designs A Replacement for Lenth’s Method for Nonorthogonal Designs Caleb King, JMP Optimal Two-level Designs Under Model Uncertainty Steven Gilmour, King’s College London Moderator: Xietao Zhou 5C: QE Invited Session Monitoring Univariate Processes Using Control Charts: Some Practical Issues and Advice Bill Woodall, Virginia Tech How Generative AI models such as ChatGPT can be (Mis)Used in SPC Practice, Education, and Research? An Exploratory Study Fadel Megahed, Miami University Moderator: David Edwards 11:45a-1:15p Luncheon Statistics Is a Core Competency for Effective Collaboration and Sound Science Madhumita (Bonnie) Ghosh-Dastidar, RAND Moderator: Jon Stallrich 1:30p – 3:00p 6A: Q&P Invited Session Active Learning for a Recursive Non-Additive Emulator for Multi-Fidelity Computer Experiments Junoh Heo, Michigan State University Quantitative Assessment of Machine Learning Reliability and Resilience Lance Fiondella, Dartmouth Moderator: Ryan Lekivetz 6B: Computer Experiments Quick Input-Response Space-Filling (QIRSF) Designs Xiankui Yang, University of South Florida A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information Andrew Brown, Clemson Moderator: Jennifer H Van Mullekom 6C: DOE II Optimal Experimental Designs for Precision Medicine with Multi-component Treatments Yeng Saanchi, JMP Simulation Experiment Design for Calibration via Active Learning Ozge Surer, Miami University Moderator: William Fisher 3:15p – 5:15p Reception, followed by SPES Special Session: How to Attract and Prepare Students for Careers in Industrial Statistics Panelists: Maria Weese, Miami University, Yeng Saanchi, JMP, Peter Parker, NASA, and Kade Young, Eli Lilly & Co. Moderator: Michael Crotty
