معرفی
Dr. Arved Bartuska is a Researcher at the Department of Mathematics, RWTH Aachen University, working in the Chair for Mathematics for Uncertainty Quantification under Prof. Raúl Tempone. His research focuses on developing efficient computational methods for Bayesian optimal experimental design, particularly in the presence of nuisance uncertainty.
Education:
- PhD (Dr. rer. nat.) from RWTH Aachen University, supervised by Prof. Raúl Tempone, with co-advisors Prof. Luis Espath (University of Nottingham) and Prof. Robert Scheichl (University of Heidelberg). Dissertation: Hierarchical Methods for Bayesian Optimal Experimental Design.
- M.Sc. and M.A. (fields not specified in the text).
Dr. Bartuska's research centers on Bayesian statistics and uncertainty quantification. He addresses computational challenges in Bayesian optimal experimental design by developing approximations like Laplace methods and leveraging Monte Carlo techniques to handle high-dimensional parameters and nuisance uncertainties in complex models.
His 2022 publication introduced a small-noise approximation for Bayesian experimental design with nuisance uncertainty, significantly reducing computational burden by avoiding nested Monte Carlo sampling. This enables practical application to engineering problems through efficient expected information gain computation.
Dr. Bartuska actively presents at international venues including the SIAM Conference on Uncertainty Quantification 2022 and the Stochastic Numerics Workshop at King Abdullah University. He maintains collaborations with institutions across Saudi Arabia, the UK, and Germany within the DFG-funded IRTG 2379 framework.
He is a core member of the Mathematics for Uncertainty Quantification chair, contributing to the International Research Training Group 2379 Modern Inverse Problems focused on interdisciplinary approaches to inverse problems from geometry, data, and models.
