Abstract

Inverse problems involving passive observation are ubiquitous in science and engineering, with applications ranging from cosmological exploration and biomedical imaging to mechanistic inference in biological systems. In contrast to scenarios with active measurements, these passive-data inverse problems present unique and formidable challenges due to their inherent nature. This talk will discuss our recent work aimed at establishing a comprehensive mathematical and statistical framework for this emerging field, highlighting foundational theoretical results and their practical implications.

Biography

Hongyu Liu is a Chair Professor in the Department of Mathematics at the City University of Hong Kong. His research focuses on inverse problems and imaging, partial differential equations, mathematical physics, scattering and spectral theory, mathematical biology, and game theory. His honors include the Calderón Prize from the International Society for Inverse Problems and the Changjiang Chair Professorship from China’s Ministry of Education. He has been named a Highly Cited Researcher by Clarivate Analytics and ranks among the top 2% of most-cited scientists worldwide. He is also a Fellow of the UK's Institute of Physics (IOP) and the Institute of Mathematics and its Applications (IMA).