KAI FU
Associate Professor
School of Mathematical Sciences,
Ocean University of China,
238 Songling Road,
Qingdao, China, 266100
Email: kfu at ouc dot edu dot cn
EDUCATION:
2007.09 - 2012.12 Ph.D. in Computational Mathematics, Shandong University, China
2010.09 - 2011.09 Visiting PhD student Department of Mathematics and Statistics, York University, Canada
2003.09 - 2007.07 B.S. in Mathematics and Applied Mathematics, Shandong University, China
WORK EXPERIENCE:
School of Mathematical Sciences, Ocean University of China, China
School of Mathematical Sciences, Ocean University of China, China
Department of Mathematics and Statistics, York University, Canada
RESEARCH INTERESTS
PUBLICATIONS
1. Fu, K., & Liang, D. (2019). A Mass-Conservative Temporal Second Order and Spatial Fourth Order Characteristic Finite Volume Method for Atmospheric Pollution Advection Diffusion Problems. SIAM Journal on Scientific Computing, 41(6), B1178-B1210.
2. Fu, K., & Liang, D. (2017). The Time Second Order Mass Conservative Characteristic FDM for Advection-Diffusion Equations in High Dimensions. Journal of Scientific Computing, 73, 26-49.
3. Liang, D., Fu, K., & Wang, W. (2016). Modelling multi-component aerosol transport problems by the efficient splitting characteristic method. Atmospheric Environment, 144, 297-314.
4. Fu, K., & Liang, D. (2016). The conservative characteristic FD methods for atmospheric aerosol transport problems. Journal of Computational Physics, 305, 494-520.
5. Fu, K., Liang, D., Wang, W., & Cui, M. (2015). The time second-order characteristic FEM for nonlinear multi-component aerosol dynamic equations in environment. International Journal of Numerical Analysis and Modeling, 12, 211-229.
6. Cui, M., Fu, K., Liang, D., Cheng, Y., & Wang, W., (2014) Numerical analysis of the second-order characteristic FEM for nonlinear aerosol dynamic equations. Journal of Computational and Applied Mathematics, 261, 48-61.
7. Fu, K., Liang, D., Wang, W., Cheng, Y., & Gong, S. (2012). Multi-component atmospheric aerosols prediction by a multi-functional MC-HDMR approach. Atmospheric Research, 113, 43-56.
GRANTS
Natural Science Foundation of China
Natural Science Foundation of Shandong province
Postdoctoral Foundation of Qingdao
Fundamental Research Funds for the Central Universities