我目前是华南师范大学软件学院的青年教师。主要研究数学最优化算法理论和分析，非光滑最优化算法和变分分析理论，对非光滑最优化算法在机器学习中的应用感兴趣。目前发表SCI期刊文章5篇，另合著2个章节。2016年我博士毕业于皇家墨尔本理工大学数学与空间科学学院，师从Andrew Eberhard教授。我的博士论文题目是“New Bundle Methods and U-Lagrangian for Generic Nonsmooth Optimization”。博士毕业后我先后在巴西国立纯数学与应用数学研究所和巴西坎皮纳斯州立大学作博士后。

Liu, S.; Eberhard, A. & Luo, Y. The U-Lagrangian, Fast Track, and Partial Smoothness of a Prox-regular Function Set-Valued and Variational Analysis, 2020, 28, 369-394 

Liu, S. A simple version of bundle method with linear programming Computational Optimization and Applications, 2019, 72, 391-412 

Liu, S.; Sagastizábal, C. & Solodov, M. Hosseini, S.; Mordukhovich, B. S. & Uschmajew, A. (Eds.) Subdifferential Enlargements and Continuity Properties of the VU-Decomposition in Convex Optimization Nonsmooth Optimization and Its Applications, Springer International Publishing, 2019, 55-87

Liu, S. & Sagastizábal, C. Bagirov, A. M.; Gaudioso, M.; Karmitsa, N.; Mäkelä, M. M. & Taheri, S. (Eds.) Beyond First Order: VU-Decomposition Methods Numerical Nonsmooth Optimization: State of the Art Algorithms, Springer International Publishing, 2020, 297-329 

Eberhard, A. C.; Luo, Y. & Liu, S. On partial smoothness, tilt stability and the mathcal VU-decomposition Mathematical Programming, 2019, 175, 155-196 

Tang, C.; Liu, S.; Jian, J. & Ou, X. A multi-step doubly stabilized bundle method for nonsmooth convex optimization Applied Mathematics and Computation, 2020, 376, 125-154

Tang, C.-m.; Liu, S.; Jian, J.-b. & Li, J.-l.A feasible SQP-GS algorithm for nonconvex, nonsmooth constrained optimization Numerical Algorithms, Springer US, 2014, 65, 1-22