讲 座 人 (SPEAKER)：赵文举 博士后，南方科技大学
时 间 (TIME)：2018.9.20(周四） 13：30-14:30
报告摘要（ABSTRACT）：
This research intends to present a numerical method for solving a real application problem in the fluid dynamic fields characterized by a stochastic inverse models. The sparse observations, noisy measurements, and highly nonlinear, non-Gaussian properties, etc. of the real problems lead to the complicated representation of the stochastic inverse solutions. To incorporate the observation data and PDE model, a probabilistic solution is constructed by the objective Bayesian inferences framework. To efficiently deal with high-dimensional properties and accelerate the numerical simulations, some advanced computational techniques in the fields of uncertainty quantity, PDE constrained optimal control, etc. are combined together. Finally, the numerical tests are presented.
报告人简介（BIOGRAPHY）：
Wenju Zhao is postdoc in department of mathematics at Southern University of Science and Technology, Shenzhen. He was awarded Master of Science degree in Computational Mathematics Jilin University. He was awarded Doctor of Philosophy degree in Computational Science at Florida State University,USA.
