1. Science and Engineering Computing Team

Science and Engineering Computing is a cross-disciplinary major that combines mathematics and engineering computation with an engineering background. The students trained in this program have a solid foundation in mathematics and are proficient in using computers to calculate engineering data. They are capable of conducting scientific research and solving practical problems in the direction of engineering and computational mathematics, as well as designing scientific and practical algorithms. Specific directions include numerical algebra, computational geophysics, numerical solutions of differential equations, etc. The team members include Liu Lan-dong, Li Jing-shuang, Zhang Li-ying, Cai Wen-li, and Zhang Lei.

2. Optimization theory and methods Team

Theory and methods of operations research. Mathematical theory of optimization. Numerical methods of nonlinear programming and integer programming. Applications of nonlinear optimization and combinatorial optimization. Optimization methods for Machine Learning.

3. The Probability and Mathematical Statistics Team

This team primarily focuses on conducting research in the areas of statistical modeling, statistical theory, statistical methods, stochastic analysis, and stochastic differential equations. We aim to address the challenges and limitations of classical statistical methods for complex data types (such as spatial data in energy, vertical data across various fields, functional data, and high-dimensional data) by developing new theories and methods including parametric and non-parametric approaches for estimation and testing. And using tools such as Brownian motion, stochastic integral and martingale theory, we explore the theoretical foundations of stochastic differential equations, backward stochastic differential equations, and stochastic partial differential equations along with their applications in optimal control and financial problems. The main research directions include:

(1) Mathematical statistics and complex data analysis;

(2) Spatial statistics and statistical computation;

(3) Stochastic analysis and stochastic differential equation.