Annie Booth

Annie Booth is an Assistant Professor in the Department of Statistics at Virginia Polytechnic Institute and State University (Virginia Tech), where she previously earned her Ph.D. in Statistics (2023). Prior to this, she served as an Assistant Professor at North Carolina State University (2023–2024). Her research focuses on Bayesian statistics, surrogate modeling, and uncertainty quantification in computer experiments, with applications in aerodynamics and engineering systems.

Education: Ph.D. in Statistics (Virginia Tech, 2023), M.S. in Statistics (Virginia Tech, 2019), B.S. in Applied Mathematics and B.A. in Psychology (Auburn University, 2018).

Research interests include deep Gaussian processes, active learning, Bayesian optimization, and reliability analysis. She has developed the open-source deepgp R-package for Bayesian deep Gaussian processes and has been recognized with awards such as the ISBA Savage Award Finalist (2023) and the Shewell Award (2023).

• Awards:
  • ISBA Savage Award Finalist (2023)
  • Shewell Award (2023)
  • Mary G. and Joseph Natrella Scholarship (2022)

Her teaching includes courses such as STAT 4714: Probability and Statistics for Electrical Engineers and STAT 3615: Biological Statistics. She actively collaborates on projects funded by organizations like Lawrence Livermore National Lab and the NSF, focusing on digital twins for clean energy production and dimension reduction techniques.