孙祥

一、个人简介

姓名：孙祥

学历：博士

职称：讲师

办公电话：无

邮箱：sunxiang@ouc.edu.cn

二、研究方向

不确定性量化、微分方程数值解以及数据驱动建模

三、研究成果

主持青岛市博士后项目1项，参与国家重点研发计划项目1项（项目骨干）.

发表文章（第一单位中国海洋大学）：

1. Xiang S., Seongyoon K., Jung-Il C. (2021). Recurrent neural network-induced Gaussian process. Neurocomputing, under review.

2. Zhen G., Yifan L., Xiang S.*,Xueying Z. (2021). A reduced order method for nonlinear parameterized partial differential equations using dynamic mode decomposition coupled with k-nearest-neighbors regression. Journal of Computational Physics, 2st round, reviews completed.

3. Xiang S., Xiaomin P., & Jung-Il C. (2021). Non-intrusive framework of reduced-order modeling based on proper orthogonal decomposition and polynomial chaos expansion. Journal of Computational and Applied Mathematics, 390, 113372.

4. Xiang S. & Jung-Il C. (2021). Non-intrusive reduced-order modeling for uncertainty quantification of space-time-dependent parameterized problems. Computers and Mathematics with Applications, 87, 50-64.