报告人：Bastian Harrach教授

报告题目： Autoencoder-based global concave optimization for Electrical Impedance Tomography (I)

报告摘要：

We aim to derive globally convergent reconstruction algorithms for the inverse coefficient problem of Electrical Impedance Tomography (aka the famous Calderón problem) and its application in lung imaging. Our main tool is to reformulate the problem as a concave semidefinite minimization problem. This allows to construct a globally convergent EIT reconstruction algorithm that is computationally feasible for a moderately low number of unknowns.

报告题目： Autoencoder-based global concave optimization for Electrical Impedance Tomography (II)

We then combine this approach with the recent data-driven observation that realistic lung images lie on a nonlinear manifold that is much lower dimensional than the space of all possible images. Variational autoencoder techniques can be used to learn such a low-dimensional parametrization, but a standard out-of-the-box autoencoder would destroy the concavity properties of the reconstruction problem. Hence, we show how to adjust the autoencoder training process in such a way that concavity (and thus global convergence of the final reconstruction strategy) is preserved.

报告时间：2025年3月12日  13：00~16：00

报告地点：理学楼609

报告人简介：Professor Bastian Harrach studied mathematics with a minor in physics at the University of Mainz and received his doctorate in 2006. After postdoc stays in Austria and Mainz, he became associate professor at the TU Munich and the University of Würzburg. In 2013, he was appointed full professor and chair (W3) of Optimization and Inverse Problems at the University of Stuttgart. He followed the call for a W3-professorship for Numerics of Partial Differential Equations at Goethe University Frankfurt in 2015. He rejected a further W3-offer to TU Berlin in 2023 in favor of the competing offer to stay at Goethe University. Since January 1, 2024, he is the Dean of the Department of Computer Science and Mathematics at Goethe University.