Kathryn Maupin is a Principal Member of the Technical Staff at Sandia National Laboratories. Motivated by a passion for transforming uncertainty into actionable insights, Kathryn leverages her extensive expertise in model validation, model form error quantification, and Bayesian analyses to drive innovative solutions that enhance research outcomes.  Kathryn earned her PhD in Computational Science, Engineering, and Mathematics, along with her M.S. in Computational and Applied Mathematics, both from The University of Texas at Austin. Her fascination with mathematical modeling began at the University of California, San Diego, where she completed her B.A. in Applied Mathematics.

When she is not immersed in data and algorithms, Kathryn enjoys the chaos of family life with her three children and three dogs. Looking ahead, Kathryn aspires to continue pushing the boundaries of computational science while encouraging others to confront ubiquitous uncertainty in their work.