Interdisciplinary Approaches to Inverse Problems via Quantum Sciences and Machine-learning-based Methods

Reference No.	2026a018
Type/Category	Grant for General Research-Workshop（Ⅰ）
Title of Research Project	Interdisciplinary Approaches to Inverse Problems via Quantum Sciences and Machine-learning-based Methods
Principal Investigator	Hisashi Morioka（Ehime University, Graduate School of Science and Engineering・Associate Professor）
Research Period
Keyword(s) of Research Fields	inverse problem, partial differential equation, numerical analysis, quantum information, machine learning
Abstract for Research Report	Inverse problems appear in various research areas of science and engineering. There are mathematical studies on uniqueness, stability and reconstruction formulas as well as numerical analysis and regularization methods for ill-posed inverse problems. For example, medical imaging and non-destructive testing are typical inverse problems. Recently, researchs on quantum algorithms is advancing alongside the development of quantum computers. From industrial perspectives, use cases of quantum computers or quantum algorithms are also important. On the other hand, some researches is adopting machine learning in order to support the studies on ill-posed inverse problems. In this workshop, we try to incorporate these topics into studies of various inverse problems as new subjects or new methodology. We also aim to enhance collaborations among applied mathematics, engineering, sciences, and industries in the context of inverse problems and various related topics. We encourage introductive presentations, since researchers from various research areas participate in this symposium. We also promote presentations by young researchers.
Organizing Committee Members (Workshop) Participants (Short-term Joint Usage)	Daisuke Kawagoe（Kyoto University・Assistant Professor） Atsushi Kawamoto（Takushoku University・Associate Professor） Yikan Liu（Kyoto University・Associate Professor） Hisashi Morioka（Ehime University・Associate Professor）