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 Professor of Mathematics at the Chinese University of Hong Kong. His research interests include inverse problems, numerical analysis and machine learning. Currently he serves on the editorial board of five journals, including inverse Problems and Journal of Computational Mathematics.

Date: December 5, 2024

Time: 9:00-11:00 am

Location: Tencent Meeting: 328347839

Sponsor: School of Mathematics, Shandong University

Abstract:

Subdiffusion is one transport mechanism found in nature, in which the mean squared particle displacement grows only sublinearly with the time. Mathematically these processes are described a diffusion type model involving a Caputo fractional derivative in time, which is nonlocal operator in time and can capture the memory phenomenon. In this talk, we discuss two inverse problems in subdiffusion, i.e., backward problem and point source identification, and illustrate the beneficial effect of the memory phenomenon for unique recovery. We shall discuss the uniqueness issue and numerical reconstructions.

For more information, please visit:

https://www.view.sdu.edu.cn/info/1020/197666.htm