
Title
Research Staff 
Email
schmidt41@llnl.gov 
Phone
(925) 4231384 
Organization
Not Available
Research Interests
Uncertainty quantification, Bayesian modeling, mixedeffects modeling, sequential design, sensitivity analysis, splines
Professional Membership
Society for Industrial and Applied Mathematics (SIAM) (SIAM)
American Statistical Association (ASA)
Ph.D., Applied Mathematics, North Carolina State University, 2016
M.S., Natural and Applied Science (Mathematics and Chemistry), Missouri State University, 2009
B.A., Mathematics, Missouri State University, 2007
W. J. Schill, R. A. Austin, K. L. Schmidt, J. L. Brown, N. R. Barton, “Simultaneous inference of the compressibility and inelastic response of tantalum under extreme loading,” Journal of Applied Physics, 130(5), pp. 055901, 2021
A. Muyskens, K. Schmidt, M. Nelms, N. Barton, J. Florando, A. Kupresanin, D. Rivera, “A practical extension of the recursive multifidelity model for the emulation of hole closure experiments,” Statistical Analysis and Data Mining: The ASA Data Science Journal, 2021.
I. J. Michaud, K. Schmidt, R. C. Smith, J. Mattingly, “A hierarchical Bayesian model for background variation in radiation source localization,” Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1002, pp. 165288, 2021.
J. Bernstein, K. Schmidt, D. Rivera, N. Barton, J. Florando, and A. Kupresanin, “Comparison of material flow strength models using Bayesian crossvalidation,” Computation Materials Science, 169(109098), 2019.
K. Schmidt, R. C. Smith, J. Hite, J. Mattingly, Y. Azmy, D. Rajan, and R. Goldhahn, “Optimal positioning of mobile sensors using mutual information,” Statistical Analysis and Data Mining: The ASA Data Science Journal, 12(6), pp. 465478, 2019.
K. Schmidt, J. Bernstein, N. Barton, J. Florando, and A. Kupresanin, “Sensitivity analysis of strength models using Bayesian adaptive splines,” AIP Conference Proceedings, 1979(140004), doi: 10.1063/1.5044954, 2018.
K. Schmidt and R. Smith, “A parameter subset selection algorithm for mixedeffects models,” International Journal for Uncertainty Quantification, 6(5), doi: 10.1615/Int.J.UncertaintyQuantification.2016016469, 2016.
R. Stefanescu, K. Schmidt, J. Hite, R. Smith, and J. Mattingly, “Hybrid optimization and Bayesian inference techniques for a nonsmooth radiation detection problem,” International Journal for Numerical Methods in Engineering, doi: 10.1002/nme.5491, 2016.