欢迎进入兰州大学数学与统计学院

常清泉

兰州大学数学与统计学院     副教授   常清泉

研究方向
非线性泛函分析与无穷维动力系统
个人简历
教育背景 
2015.09–2019.12     兰州大学,数学与统计学院,理学博士,基础数学专业,导师:孙春友教授
2012.09–2015.07     兰州大学,数学与统计学院,理学硕士,应用数学专业,导师:马闪教授 
2008.09–2012.07     山西大学,数学科学学院,数学与应用数学专业,本科

工作经历 
2020.06 – 2025.06    广州大学,数学与信息科学学院,数学学科博士后流动站博士后,合作导师:曹道民研究员
2025.12-至今            兰州大学数学与统计学院,副教授
教学及指导学生情况
发表论文及专著
[1] Q. Chang and D. Li, “Well-posedness and dynamics of wave equations with nonlinear damping and moving boundary,” Discrete and Continuous Dynamical Systems-B, pp. 0–0, 2024.  
[2] Q. Chang and D. Li, “Well-posedness and dynamics of 2d navier–stokes equations with moving boundary,” Journal of Mathematical Physics, vol. 64, no. 2, p. 022 702, 2023. 
[3] Q. Chang, D. Li, C. Sun, and S. V. Zelik, “Deterministic and random attractors for a wave equation with sign changing damping,” Izvestiya. Mathematics, vol. 87, no. 1, pp. 161–210, 2023. 
[4] Q. Chang and D. Li, “Continuity of dynamical behaviors for strongly damped wave equations with perturbation,” Journal of Mathematical Physics, vol. 63, no. 5, p. 052 702, 2022. 
[5] D. Li, Q. Chang, and C. Sun, “Pullback attractors for a critical degenerate wave equation with 
time-dependent damping,” Nonlinear Analysis: Real World Applications, vol. 63, p. 103 421, 2022. 
[6] Q. Chang, D. Li, and C. Sun, “Random attractors for stochastic time-dependent damped wave equation with critical exponents,” Discrete Continuous Dynamical Systems - B, vol. 22, no. 11, 2020.7 
[7] Q. Chang, D. Li, and C. Sun, “Dynamics for a stochastic degenerate parabolic equation,” Computers mathematics with applications, vol. 77, no. 9, pp. 2407–2431, 2019. 
[8] J. Wang, Q. Chang, Q. Chang, Y. Liu, and N. R. Pal, “Weight noise injection-based mlps with group lasso penalty: Asymptotic convergence and application to node pruning,” IEEE Transactions on Cybernetics, pp. 1–19, 2018. 
[9] D. Li, C. Sun, and Q. Chang, “Global attractor for degenerate damped hyperbolic equations,” Journal of Mathematical Analysis Applications, vol. 453, no. 1, pp. 1–19, 2017. 
[10] J. Wang, Q. Cai, Q. Chang, and J. M. Zurada, “Convergence analyses on sparse feedforward neural networks via group lasso regularization,” Information Sciences, vol. 381, pp. 250–269, 2017.
项目成果
国家自然科学基金青年科学基金项目,变区域上三类发展方程解的长时间动力学行为研究,No. 12201142
荣誉、获奖
社会工作
其它信息

作者:常清泉