哈尔滨工业大学（深圳）学术讲座

演讲人Speaker：   香港中文大学 金邦梯  教授

题目Title: Conductivity Imaging Using Deep Neural Networks

时间Date：2023年 11 月 02 日       Time：10:00–11:00

地点Venue：腾讯会议934-203-154

链接：https://meeting.tencent.com/dm/rrcJWzv0pUA5

内容摘要Abstract： 

Conductivity imaging from various observational data represents one fundamental task in medical imaging. In this talk, we discuss numerical methods for identifying the conductivity parameters in elliptic PDEs. Commonly, a regularized formulation consists of a data fidelity and a regularizer is employed, and then it is discretized using finite difference method, finite element methods or deep neural networks in practical computation. One key issue is to establish a priori error estimates for the recovered conductivity distribution. In this talk, we discuss our recent findings on using deep neural networks for this class of problems, by effectively utilizing relevant stability results.

个人简介(About the speaker):

Bangti Jin received a PhD in Mathematics from the Chinese University of Hong Kong, Hong Kong in 2008. Previously, he was Lecturer and Reader, and Professor at Department of Computer Science, University College London (2014-2022), an assistant professor of Mathematics at the University of California, Riverside (2013–2014), a visiting assistant professor at Texas A&M University (2010–2013), an Alexandre von Humboldt Postdoctoral Researcher at University of Bremen (2009–2010). Currently he is a Professor of Mathematics at the Chinese University of Hong Kong. His research interests include inverse problems, numerical analysis and machine learning.