Partial Differential Equation is an important mathematical tool for computer science. This one month short course is designed to give first year Ph.D. students a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by people who are doing research related to PDE. The topics of the course draw mainly from types of image and video processing, from geometrical modeling, and from statistical algorithmics.

Students entering the class should have a pre-existing working knowledge of fundamental mathematics and algorithms, though the class has been designed to allow students with a strong numerate background to catch up and fully participate.

1. Arieh Lserles. A first course in the numerical analysis of differential equations. (微分方程数值分析基础教程, 清华大学出版社)
2. 余德浩, 汤华中. 微分方程数值解法. 科学出版社.
3. Stanley Osher, Ron Fedkiw. Level Set Methods and Dynamic Implicit Surfaces.