题    目：A Scientific Machine Learning Approach for Data Assimilation

主讲人：凤小兵 教授

单    位：美国田纳西大学

时    间：2024年7月7日 8:20 – 9:20

地    点：数学与统计学院一楼报告厅

摘    要：Data assimilation aims to optimally integrate model prediction and observation data to achieve a better estimation and predication for the state variables which are governed by the model. It has been the cornerstone for the modern weather forecast. In this talk, I shall first give a brief overview of data assimilation methodologies and their numerical techniques. I shall then present a scientific machine learning perspective for data assimilation problems and resulting efficient numerical algorithms based on the new perspective.

简    介：Xiaobing Feng is a mathematics professor and the math department head at the University of Tennessee. His received both his BS and MS degree in Mathematics from Xian Jiaotong University in 1983 and 1985 respectively, and his PhD in Computational and Applied Mathematics from Purdue University in 1992 under the direction of the late Professor Jim Douglas, Jr. His main research area is Computational and Applied Mathematics with a focus on numerical nonlinear deterministic and stochastic PDEs and their applications in sciences and engineering.