Current and Graduated Students
Coleman is working on a remote sensing project with the Naval
- Rui Meng is
working on projects with Lawrence Livermore National Laboratory.
Linscome-Hatfield, MS 2019,
worked on surrogate modeling for variable selection in computer simulation experiments.
- Matt Simms,
PhD 2019, co-advised by Hongyun Wang,
worked on statistical inference for nanopore experiments.
- Tony Pourmohamad, PhD
2016, worked on constrained optimization using a filter approach.
- Kenna Nelson, MS 2015,
worked on optimizing locus of control for aircraft flights.
- Brenton Blair, MS 2015,
worked on classification for damaged aircraft trajectories.
- Nick Grunloh, MS 2014,
worked on assessing convergence for statistical optimization.
- John Guenther, PhD 2013,
worked on finding, characterizing, and choosing among multiple optima, as well
as simultaneous optimization and sensitivity analysis.
- Morgan Mendoza, MS 2012, developed algorithms for generating geologically realistic permeability grids as simulator inputs
- Samantha Crane, MS 2012, explored combining statistical modeling with a filter approach for constrained optimization
- Yuning He, PhD 2012,
worked on computer model emulation for complex simulators
with multivariate functional output.
- Waley Liang, PhD 2012, worked on partitioning
for the convolution approach to Gaussian processes, to allow
nonstationary modeling of large spatial datasets.
- Jing Chang, PhD 2011,
worked on model selection for neural networks and computer models.
- 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.
- Xin Zhang, MS 2010, explored scaling issues for mixed-integer surrogate modeling
- Angela Pignotti,
PhD 2009, worked on
methodology for comparing spatially correlated fields, with an
application to global and regional climate modeling.
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.
- 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.
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.
Holloman, PhD 2002 from Duke University, co-supervised with Dave
Higdon, worked on multiscale methods for spatial inverse problems,
including multiscale genetic algorithms.