个人简历

教育背景
2009.09－2014.06重庆大学数学与统计学院(计算数学专业，硕博连读)，理学博士学位。
2005.09－2009.06重庆大学数学与统计学院(数学与应用数学专业)，理学学士学位。
工作和研究经历
2017. 01－至今 西南财经大学，经济数学学院，副教授。
2014. 07－2016. 12 西南财经大学，经济数学学院，讲师。
2016. 12—2017. 11 University of Pisa, Department of Mathematics, Visiting Scholar.

研究领域

1. 最优化理论及其应用
2. 集值与变分分析
3. 像空间分析

近期论文

1.Zhu, S.K. 2018. Image space analysis to Lagrange-type duality for constrained vector optimization problems with applications. Journal of Optimization Theory and Applications, 177(3): 743–769. (SCI)
2.Zhu, S.K. 2016. Weak sharp efficiency in multiobjective optimization. Optimization Letters, 10: 1287-1301. (SCI)
3.Zhu, S.K., Li, S.J. 2016. New second-order contingent epiderivatives and set-valued optimization problems. Acta Mathematicae Applicatae Sinica, English Series, 32: 983-994. (SCI)
4. Zhu, S.K., Li, S.J., Teo, K.L. 2014. Second-order Karush-Kuhn-Tucker optimality conditions for set-valued optimization. Journal of Global Optimization, 58: 673-692. (SCI)
5. Zhu, S.K., Li, S.J. 2014. Unified duality theory for constrained extremum problems. Part I: Image space analysis. Journal of Optimization Theory and Applications, 161: 738-762. (SCI)
6. Zhu, S.K., Li, S.J. 2014. Unified duality theory for constrained extremum problems. Part II: Special duality schemes. Journal of Optimization Theory and Applications, 161: 763-782. (SCI)
7. Zhu, S.K., Li, S.J. 2013. Optimality conditions of strict minimality in optimization problems under inclusion constraints. Applied Mathematics and Computation, 219: 4816-4825. (SCI)
8. Zhu, S.K., Li, S.J., Xue, X.W. 2012. Strong Fermat rules for constrained set-valued optimization problems on Banach spaces. Set-Valued and Variational Analysis, 20: 637-666. (SCI)
9. Li, S.J., Zhu, S.K., Li, X.B. 2012. Second-order optimality conditions for strict efficiency of constrained set-valued optimization. Journal of Optimization Theory and Applications, 155: 534-557. (SCI)
10. Li, S.J., Zhu, S.K., Teo, K.L. 2012. New generalized second-order contingent epiderivatives and set-valued optimization problems. Journal of Optimization Theory and Applications, 152: 587-604.