Abstract:  

Transfer operators play important roles in data-driven discovery for dynamical systems. In the talk, I will address three problems: (1) Koopman operator-based data-driven methods are used to model the state and probability evolution for nonlinear dynamical systems; (2) Perron-Frobenius operator filter is presented for data assimilation; (3) The Koopman modes and eigenvalues are estimated by ensemble Kalman filtering.

Bio:  

Lijian Jiang, Professor of Mathematics at Tongji University. His research interests include multiscale computational methods，data-driven modeling and uncertainty quantification.  He jointed Tongji University from 2018. He had previously been a math professor at Hunan University from 2013 to 2017.  He had worked in oil well industry in USA as a chief scientist， and   at IMA in University of Minnesota and LANL as postdoctoral fellows.  He has been editorial members for several journals such as JCAM and JCMDS.  

组织者：邓权灵