I am an Assistant Professor in the Department of Statistics at Virginia Tech. Previously, I was an Assistant Professor of Statistics at NC State University. I earned my Ph.D. in Statistics at Virginia Tech in 2023, and my Ph.D. dissertation was recently selected as a finalist for the 2023 Savage Award. I specialize in surrogate modeling of computer experiments including uncertainty quantification, active learning, Bayesian optimization, and reliability analysis. My recent focus has been on developing deep Gaussian processes as surrogate models; I maintain the open-source deepgp R-package on CRAN.

NOTE: I previously published under my maiden name, Annie Sauer.

News and Highlights

• I will be leading a full-day short course on “High Quality Coding for High Quality Analytics” at this year’s Fall Technical Conference
• Starting in 2025, I am returning to the Virginia Tech Department of Statistics after 1.5 years at NC State. Go Hokies!

• New paper on classification with Bayesian (deep) GPs accepted in Quality Engineering
• New paper on Bayesian deep Gaussian processes for cosmological matter power spectra on arXiv
• New paper on surrogate design for failure probability estimation on arXiv
• New paper on monotonic warpings for deep Gaussian processes just accepted to Statistics and Computing
• New paper on contour location with deep Gaussian processes published in the Annals of Applied Statistics
• New collaboration with Kevin Quinlan and Laura Wendelberger to study dimension reduction with deep Gaussian processes, funded by Lawrence Livermore National Lab
• I’m starting work on a new project funded by the NSF to study digital twins of rotating detonation combustors for clean energy production, with James Braun
• New paper on Bayesian optimization with Voronoi candidates on arXiv

To keep this page short and sweet, old news is archived here.