MATH Seminar

Title: An optimal Bayesian estimator for a stochastic problem in Diffuse Optical Tomography
Seminar: Numerical Analysis and Scientific Computing
Speaker: Anuj Abhishek of University of North Carolina at Charlotte
Contact: Elizabeth Newman, elizabeth.newman@emory.edu
Date: 2021-11-19 at 12:30PM
Venue: MSC W201
Download Flyer
Abstract: Studying coefficient inverse problems in a stochastic setting has increasingly gained in prominence in the past couple of decades. In this talk, we will present some results that were obtained for a Bayesian estimator built from the noisy data obtained in a simplified one-parameter Diffuse Optical Tomography (DOT) Model. We establish the rate of convergence of such an estimator in the supremum norm loss and show that it is optimal. This work extends the approach proposed by Abraham and Nickl in a recent article (On Statistical Calderon problems) and applies it to the problem in DOT setting. We also present some preliminary numerical simulations in support of our theoretical findings. This is joint work with Dr. Taufiquar Khan (UNCC) and Dr. Thilo Strauss (Robert Bosch GmbH).