2020-03-25 ~ 2020-03-29 271
Organizers: Jin Cheng (Fudan), Jijun Liu (Sotheast Univ), Gen Nakamura (Hokkaido Univ), Lingyun Qiu (Tsinghua), Dinghua Yang (Tsinghua)
Synopsis: This conference will serve as a venue for presenting and discussing recent advances and challenges in the rapidly growing field of inverse problems and media imaging, while enabling new collaborations. We aim to bring together experts in applied mathematics working on modeling, computation, and applied analysis in media sciences, material sciences, inverse problems and related topics. These topics are at the research fronts of modern applied mathematics, with important applications in clinical medicine, manufacturing processes in engineering, new materials, imaging sciences, and geophysics. Research on all aspects of the computational imaging pipeline from data acquisition and processing to system simulation and image reconstruction, processing, and analysis will be discussed. Given the rapid development of data-driven machine learning techniques, the conference will partly focus on recent trends in emerging these approaches into imaging sciences. The fusion of the inverse problems and machine learning is essentially still wide open, and new models in machine learning put forward exciting opportunities. Analysis, algorithms, and computational issues raised from those fields will greatly enrich the development of applied mathematics theories and inspire new interesting directions of research.