Current and Graduated Students

  1. Nick Grunloh is working on nonparametric modeling of fish populations.
  2. Sampson Mao, MS 2021, co-advised by Robert Lund, worked on methods for transforming Gaussian random fields to get fields with other distributions, such as correlated counts.
  3. Amanda Coleman, MS 2020, worked on a remote sensing project with the Naval Postgraduate School.
  4. Rui Meng, PhD 2020, worked on temporal stochastic process model projects with Lawrence Livermore National Laboratory.
  5. Travis Linscome-Hatfield, MS 2019, worked on surrogate modeling for variable selection in computer simulation experiments.
  6. Matt Simms, PhD 2019, co-advised by Hongyun Wang, worked on statistical inference for nanopore experiments.
  7. Tony Pourmohamad, PhD 2016, worked on constrained optimization using a filter approach.
  8. Kenna Nelson, MS 2015, worked on optimizing locus of control for aircraft flights.
  9. Brenton Blair, MS 2015, worked on classification for damaged aircraft trajectories.
  10. Nick Grunloh, MS 2014, worked on assessing convergence for statistical optimization.
  11. John Guenther, PhD 2013, worked on finding, characterizing, and choosing among multiple optima, as well as simultaneous optimization and sensitivity analysis.
  12. Morgan Mendoza, MS 2012, developed algorithms for generating geologically realistic permeability grids as simulator inputs
  13. Samantha Crane, MS 2012, explored combining statistical modeling with a filter approach for constrained optimization
  14. Yuning He, PhD 2012, worked on computer model emulation for complex simulators with multivariate functional output.
  15. Waley Liang, PhD 2012, worked on partitioning for the convolution approach to Gaussian processes, to allow nonstationary modeling of large spatial datasets.
  16. Jing Chang, PhD 2011, worked on model selection for neural networks and computer models.
  17. Tracy Holsclaw, PhD 2011, co-advised by Bruno Sansó, worked on modeling of unknowns in the equation of state in cosmology, to help our understanding of dark energy.
  18. Xin Zhang, MS 2010, explored scaling issues for mixed-integer surrogate modeling
  19. Angela Pignotti, PhD 2009, worked on methodology for comparing spatially correlated fields, with an application to global and regional climate modeling.
  20. Matt Taddy, PhD 2008, did his thesis work primarily with Thanasis Kottas on Bayes nonparametrics, but also worked with me on computer modeling and optimization using treed Gaussian processes.
  21. Weining Zhou, PhD 2006, co-advised by Bruno Sansó, worked on spatial problems, in particular an inverse problem for a proton accelerator and an environmetric application with Bruno Sansó.
  22. Bobby Gramacy, PhD 2005, won the Savage Award for his thesis on treed Gaussian processes, a flexible yet computationally efficient approach for nonstationary spatial modeling and heteroscedastic semiparametric regression.
  23. Chris Holloman, PhD 2002 from Duke University, co-supervised with Dave Higdon, worked on multiscale methods for spatial inverse problems, including multiscale genetic algorithms.