Özge Sürer
Assistant Professor Miami University
Developing statistical methods for learning from complex simulations and data.
About
My research focuses on developing statistical methods for complex computer models and simulation-based systems. I am particularly interested in uncertainty quantification, statistical calibration, computer experiments, and active learning, with applications to scientific computing and digital twins.
Prior to joining Miami University, I was a postdoctoral research fellow at the Northwestern Argonne Institute of Science and Engineering (NAISE), where I worked on Bayesian uncertainty quantification and computational statistics. I received my Ph.D. in Industrial Engineering and Management Sciences from Northwestern University in 2020.
Research Interests
Uncertainty Quantification
Bayesian methods for quantifying uncertainty in complex computational models.
Computer Experiments & Calibration
Statistical design, emulation, and calibration of deterministic and stochastic computer models.
Active & Sequential Learning
Adaptive experimental design for efficiently learning from expensive simulations and data.
Education
Ph.D.
Industrial Engineering and Management Sciences
M.S.
Industrial Engineering
B.S.
Industrial Engineering