报告题目：Data assimilation from a viewpoint of regularization theory

报 告 人：陆帅教授（复旦大学）

报告时间：2022年12月21日  16:00

报告地点：腾讯会议（962 879 660）

报告摘要：

Inverse problems are ubiquitous in real applications. Understanding of algorithms for their solution has been greatly enhanced by a deep understanding of the linear inverse problem. In the applied communities ensemble-based filtering methods have recently been used to solve inverse problems by introducing an artificial (continuous) dynamical system. This opens up the possibility of using a range of other filtering methods, such as 3DVAR, Kalman-Bucy filter (online) and 4DVAR (offline), to solve inverse problems, again by introducing an artificial dynamical system. The aim of this talk is to understand these methods in the context of the regularization theory under the framework of linear inverse problems.

报告人简介：

陆帅，复旦大学数学科学学院教授，主要从事数学物理反问题计算方法与数学理论的研究，特别是反问题正则化方法收敛性分析及偏微分方程反问题稳定性理论等。至今在Inverse Problems、SIAM系列、Numer. Math.、Math. Comp.等权威期刊共发表学术论文五十余篇，合作出版英文学术专著一本。2019年获得国家杰出青年科学基金资助，现任《Inverse Problems》的编委，曾获上海市自然科学奖一等奖（第二完成人）。