2026 Program – Fall Technical Conference

Access the program book here

At-a-Glance Schedule – Tuesday, October 6

8:00a – 12:00p	Half-Day Short Course: From Prompt to Deployment: Using Coding Assistants to Generate Reproducible Quarto Reports for Quality Data Analysis Scott Mutchler, Virginia Tech
12:00p – 1:00p	Lunch Break
1:00p – 5:00p	Half-Day Short Course: OMARS Designs: Modern Experimental Designs for Simultaneous Screening and Response Surface Optimization Peter Goos, University of Leuven
5:30p – 7:00p	Fall Technical Conference Opening Social Join us for an informal opening social at the South Park Suffolk Punch Brewing. Attendees may purchase their own food and beverages

At-a-Glance Schedule – Wednesday, October 7

8:00a–8:30a	Breakfast Barringer
8:30a–9:15a	Welcome & Plenary Session Gerald J. Hahn Achievement Award Barringer The Ubiquity of Variation: Implications for Statisticians Willis Jensen, Brigham Young University
	Selwyn	Clayton I	Clayton II
9:30a–10:15a	1A: CPID Invited Design and analysis of experiments assessing handheld RFID readers in complex environments Justin Strait, LANL Moderator: Luke Hagar	1B: Program Committee Invited The perfect is the enemy of the good Bradley Jones Moderator: Adam Pintar	1C: SPES Invited Rethinking Time Series as Sequence Modeling: New Attention Architectures and How AI Agents Automate the Research Shihao Yang, Georgia Institute of Technology Moderator: Chia-Ruei Liu
10:30a–12:00p	2A: Design of Experiments Use of Split-Plot Optimal Design for Optimization of a Constrained Two-Step Chemical Reaction Process: A Case Study Example Richard Montes, Alnylam Pharmaceuticals Powerful Experimental Designs for Multiple Hypothesis Tests Jonathan Stallrich, North Carolina State University Sample Size and Design Optimization with Transition Costs Peter Goos, KU Leuven Moderator: Todd Coffey	2B: ISEA Data Quality: Missed Opportunity or Golden Opportunity? Roger Hoerl, Union College Experimental Design for Digital Twins with Many Qualitative Factors via ML/AI-Accelerated Integer Programming Yen-Chun Liu, Duke Moderator: Caleb King	2C: Machine Learning Are “Fair Aware” Machine Learning Algorithms Really Fair? Frederick W. Faltin, Virginia Tech Bayesian Optimization for Hyperparameter Tuning in AI Models Linfeng Lyu, Clemson University Fitting an Escalier to a Curve Sebastien Bossu, University of North Carolina at Charlotte Moderator: Yeng Saanchi
12:00p–1:15p	Luncheon and Award Presentation Barringer
1:30p–3:00p	3A: Bayesian Methods and AI Reliability Credible Distributions of Overall Ranking of Entities Abhyuday Mandal, University of Georgia From Reviews to Insights: A Rank-Based Bayesian Model for Multimodal Aspect Sentiment Aggregation Kaiwen Wang, Davidson College AI-SALT: A Screening Accelerated Life Testing Framework for AI System Reliability Simin Zheng, Virginia Tech Moderator: Jared Clark	3B: Panel – Journal Editors Panelists Rong Pan, Arizona State University Kamran Paynabar, Georgia Institute of Technology Bill Woodall, Virginia Tech Moderator: Maria Weese	3C: Applied Data Science & AI CROSSVALI: A Method for Prompting AI for Data Analysis Jennifer Van Mullekom and Anne Driscoll, Virginia Tech An Explainable Artificial Intelligence Framework for Child Trafficking Risk Assessment Abiodun Olalere, North Carolina Agricultural and Technical State University Space-Filling One-Factor-At-A-Time Designs Wei-Yang Yu, Georgia Tech Moderator: Ashley Childress
3:00p–3:30p	Break:
3:30p–4:30p	W. J. Youden Address Barringer Large Computer Experiments: When Interpolation Becomes Extrapolation Derek Bingham, Simon Fraser University
4:30p–6:00p	Reception and Poster Session I Clayton I and II Monitoring Supervised Learning Models with Statistical Control Charts Leah Jones, Virginia Tech Modeling Environmental Predictors of Grizzly Bear Scavenging in Yellowstone National Park Becky Catlett, Virginia Tech A Two-Stage Structural Equation Modeling Framework to Address Spatial Confounding in Binary Response Models Md. Hasibul Islam Jitu, North Carolina State University Estimation Stability Under Low Sample-Size-to-Parameter Conditions: Comparing Classical OLS and Regularized Bayesian Regression Estimators Naa Adoley Acquaye, University of Denver Sequential Reliability Testing for LLM Code Generation Vu Huynh, Virginia Tech Super-convergent Subsampling Estimators for M-Estimation Jiaqi Liu, University of Connecticut Estimating Decision Uncertainty from Preference Uncertainty: Application to Ground Vehicle Design Chia-Ruei Liu, Clemson University Respecting the Boundaries: Space-Filling Designs for Surrogate Modeling with Boundary Information Yen-Chun Liu, Duke University csbewma: An R Package for Cumulative Standardized Binomial EWMA Control Charts Faruk Muritala, Kennesaw State University Conformal Prediction for Intrusion Detection Chidiogo Onoh, University of Central Florida

At-a-Glance Schedule – Thursday, October 8

8:00a–8:30a	Breakfast Barringer
	Selwyn	Clayton I	Clayton II
8:30a–9:15a	4A: STAT Invited Session Probability of Detection: Evaluating the Reliability of Nondestructive Inspection Systems Christine Knott, Air Force Research Laboratory Moderator:Karen Hulting	4B: Program Committee Invited Supersaturated Designs for Main Effects and Two‐Factor Interactions: Supersaturated Designs for Interactions Maria Weese, Miami University Moderator: Jonathan Stallrich	4C: Q&P Invited Conjecturing-Based Discovery of Patterns in Data David Edwards, The Citadel Moderator: Courtney Kyger
9:30a– 10:30a	5A: Computer Experiments Revisiting the 10p Rule for Computer Experiments Miles Woollacott, North Carolina State University Profile Bayesian Optimization in Expensive Computer Experiments Courtney Kyger, Virginia Tech Moderator: Simin Zheng	5B: Optimization and DOE Optimal Sparse Projection Design for Systems with Treatment Cardinality Constraint Kexin Xie, Virginia Tech An Economical Approach to Design with Precision Criteria Luke Hagar, University of British Columbia Moderator: Yen-Chun Liu	5C: Quality Metrics Quantile-Based PCIs for Evaluating Two Processes M Z Anis, Indian Statistical Institute Predictive Ppk Calculations for Biologics and Vaccines using a Bayesian approach Jianfang Hu, Pfizer Moderator: M. Z. Anis
10:30a– 11:00a	Break
11:00a–12:30p	6A: Industrial Statistics XCT Systems Transfer Function Methodology Development Pathfinder: Linking System Performance Using Experimental Design Mindy Hotchkiss, Enquery Research LLC Distributed Accelerated Failure-Time Models for Big Data Jared Clark, Virginia Tech A Feature-Enhanced Capacity Prediction Method for Efficient Lithium-Ion Cell Grading under Multi-Temperature Conditions Shih-Han Huang, Virginia Tech Moderator: Naa Adoley Acquaye	6B: Panel – Beyond the Tenure Track: Careers in Industry and Applied Research Panelists Ashley Childress, Eli Lilly Todd Coffey, Pfizer Abby Nachtsheim, LANL Moderator: Michael Crotty	6C: Bayesian and Reliability Mechanism-Level Bayesian Inference for Latent Gaussian Models: A Scalable Framework for Spatial Flow Michael R. Schwob, Virginia Tech Feature learning and selection for non-linear regression Ayumi Mutoh, North Carolina State University Validating Applications Based on Machine Learning Libraries Using Blocked Covering Arrays: A Case Study Yeng Saanchi, JMP Statistical Discovery LLC & Sohyeon Kim, North Carolina State University Moderator: Becky Catlett
12:30p–1:45p	Luncheon Barringer Quality by Design: Strategy, AI, and Communities in Action Jeri Mulrow, 2026 President of the American Statistical Association
2:00p–3:30p	7A: Experimental Design and System Evaluation Combinatorial Testing of Engineered Systems with Hard-to-Change Factors William Fisher, JMP Statistical Discovery LLC Dark Uncertainty Imperils Hybrid Metrology for Semiconductors Adam L. Pintar, National Institute of Standards and Technology Monitoring Parametric, Robust D-Optimal Designs for Ordinal Split-Plot Experiments via a Pairwise Composite Likelihood Surrogate Marcus B. Perry, University of Alabama Moderator:Leah Jones	7B: Panel – From Bench to Batch: Nonclinical Statistics Case Studies from the Pharmaceutical Industry Panelists Briana Russo, Merck Greg Steeno, Pfizer Kade Young, Eli Lilly Moderator: Katie Brickey	7C: Emerging Statistical Methods and Applications An Interpretable Generative Framework for Statistical Process Control in High-Dimensional Settings Waldyn Martinez, Miami University Diffusion Non-Additive Model for Multi-Fidelity Simulations with Tunable Precision Junoh Heo, Wake Forest University New Perspectives of Respondent-Driven Sampling with Application to Sex-Trafficked Population in Senegal Hui Yi, North Carolina Agricultural and Technical State University Moderator: Faruk Muritala
3:30p – 5:00p	Reception and Poster Session II Barringer Sparse Bayesian Optimization on the Simplex via Manifold-Aware Kernels Vivek Singh, Duke University Exploring Intrinsic Gaussian Processes as Priors for Estimation Problems Colby Stakun-Pickering, Virginia Tech A Comparative Simulation Study of Signal/Response and Hit/Miss Methodologies for POD Analysis Kaelan Swallow, Strategic Ohio Council for Higher Education A Geometric Approach to High-Dimensional Statistical Process Control via Manifold Fitting Ismail Burak Tas, The Pennsylvania State University Multiclass Calibration Assessment and Recalibration of Probability Predictions via the Linear Log Odds Calibration Function Amy Vennos, Virginia Tech Sequential IMSE Design for Manifold-Regularized Kernel Logistic Regression Xiaotian Wang, University of Georgia Sequentially Weighted One-Factor-at-a-Time Designs for Safe Online Controlled Experiments Rachel Winpisinger, North Carolina State University Monitoring 75,000 Calorimeter Channels: Coupled, Anytime-Valid Sparse Changepoint Detection Patrick Woitschig, Duke University