Title: Statistical Approaches for Addressing Interdisciplinary Problems

Presenter: Joanne R. Wendelberger

Time: September 26, 2024, 5:30PM CEST / 11:30 AM EST / 8:30 AM PST

Abstract: Interdisciplinary problem-solving draws upon expertise from multiple fields and often requires teams of individuals from different disciplines working in collaboration to address complex challenges. Statisticians can play a pivotal role in the process of addressing interdisciplinary challenges by providing a statistical framework for modeling and analysis. In this presentation, statistical distributions and metrology concepts will be used to provide a foundation for modeling errors, constructing different types of statistical intervals, and characterizing error transmission to support further modeling and analysis. Examples of statistical solutions will be discussed that involve methods and approaches from Design and Analysis of Experiments, Functional Data Analysis, Data Science, and Predictive Analytics that were developed as part of the collaborative process of interdisciplinary problem-solving.

Bio: Dr. Joanne Wendelberger is a Guest Scientist in the Statistical Sciences Group at Los Alamos National Laboratory, following her 32 year career as a Statistician and R&D Manager at Los Alamos. She completed her Master’s and Ph.D. degrees in Statistics at the University of Wisconsin-Madison, where she was a student of Professor George Box. She received her Bachelor’s Degree from Oberlin College, majoring in Mathematics and Economics. Prior to her time at Los Alamos, Dr. Wendelberger worked as a Statistical Consultant at the General Motors Research Laboratories. Throughout her career, Dr. Wendelberger’s research has been motivated by the need to develop solutions to complex interdisciplinary problems, particularly in the physical and engineering sciences. Her research interests include statistical experimental design and test planning, statistical bounding and error analysis, materials degradation modeling, analysis of discrete simulations, sampling and analysis for large-scale computation and visualization, functional data analysis, and institutional analytics. Her publications have included work on orthogonal and near-orthogonal designs, uncertainty in designed experiments, repeated measures degradation studies, metrology, randomized selection on the GPU, data sampling using bitmap indexing, in situ sampling of a large-scale particle simulation, and colormaps for improving data perception. Dr. Wendelberger is a Fellow of the American Statistical Association and a Senior Member of the American Society for Quality which has recognized her as the W J. Youden Memorial Address lecturer at the Fall Technical Conference and as recipient of the William G. Hunter Award. She is currently an Associate Editor for Technometrics and has previously served as a member of the Technometrics Management Committee as well as numerous conference and awards committees. She has also mentored students at Los Alamos National Laboratory and shared her knowledge of Statistics at a variety of K-12 educational outreach activities.

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