主要从事最优化理论、算法及应用，智能信息处理、机器学习、支持向量机等方面的研究，发表论文30余篇，被SCI检索20余篇、被EI检索30余篇。主持完成国家自然科学基金2项，主要参与完成国家自然科学基金4项，主持在研国家自然科学基金1项(52万元). 

发表论文：

51. 安亚利,周水生,陈丽,王保军. 鲁棒支持向量机及其稀疏算法, 西安电子科技大学学报 Vol.46, No.1,pp.64-72,2019. (doi: 10.19665/j.issn1001-2400.2019.01.011)(EI:20191606810422).

50. Zhou, Shuisheng,Zhang, Danqing. Bilateral Angle 2DPCA for Face Recognition, IEEE SIGNAL PROCESSING LETTERS, vol.26, No.2, pp.317-321, 2019. (WOS:000455914600008)

49. Ma, Jiajun,Zhou, Shuisheng, etc. A sparse robust model for large scale multi-class classification based on K-SVCR, PATTERN RECOGNITION LETTERS,vol.117, pp.16-23, 2019. (WOS:000455196900003)

48. Shuisheng Zhou,Baojun Wang,Li Chen.High precision approximate analytical solutions to ODE using LS-SVM, The Journal of China Universities of Posts and Telecommunications, 25(4):94-102,2018. (EI:20185206315686)

47. Li Chen, Shuisheng Zhou, Zhuan Zhang. SVRG for a non-convex problem using graduated optimizatin algorithm, Journal of Intelligent & Fuzzy Systems, Vol. 34, No. 1, pp.153-165, 2018.
46. Li Chen, Shuisheng Zhou. Sparse algorithm for robust LSSVM in primal space, Neurocomputing, Vol 275(31):2880-2891, 2018. (pdf, code)
45. Li Chen,Shuisheng Zhou, et al. Fast kernel fuzzy c-means algorithms based on difference of convex programming.  ICNC-FSKD,2016,Agu. pp.1090-1095.
44. 周水生等. 基于Cholesky分解的K2DPCA人脸识别研究, 系统工程理论与实践， 2016，36(2)：528-535.  (pdf, code)
43. Shuisheng Zhou. Sparse LSSVM in primal using Cholesky Factorization for large-scale problems.  IEEE Transactions on Neural Networks and Learning Systems, 27(4):783-795, 2016.  (pdf, code)
42. Manfred K.Warmuth, Wojciech Kotłowskib, Shuisheng Zhou. Kernelization of matrix updates, when and how? Theoretical Computer Science, 2014, pp.159-178. DOI: 10.1016/j.tcs.2014.09.031.
41. 史加荣、周水生、郑秀云 ，多线性鲁棒主成分分析. 电子学报, 08期, pp 1480-1486, 2014/8/15.
40. 赵扬扬、周水生、武亚静 ，一种用于人脸识别的非迭代GLRAM算法 ，西安电子科技大学学报, 02期, pp 144-150, 2014.
39. Shuisheng Zhou. Which is better? Regularization in RKHS vs Rm for RSVMs, Statistics, Optimization and Information Computing, 1 (1), 82-106, 2013 . DOI: 10.19139/soic.v1i1.27. (pdf, code)
38. Shuisheng Zhou, Jiangtao Cui, et al. New Smoothing SVM Algorithm with Tight Error Bound and Efficient Reduced Techniques. Computational Optimization and  Applications, 56(3), 599-617, 2013. (pdf, code)
37. Shuisheng Zhou, Feng Ye et al. Exact Sparse LS-SVM. in Proceedings of  the 5th International Conference on Optimization and Control with Applications (OCA2012), pp143-148, Beijing, China, December 4-8, 2012.
36. Warmuth, Manfred K,Kotowski, Wojciech; Zhou, Shuisheng. Kernelization of matrix updates, when and how? Algorithmic Learning Theory - 23rd International Conference, ALT 2012,v. 7568 LNAI, p350-364, 2012.
35. Yinli Dong, Shuisheng Zhou. SVM Regularizer Models on RKHS vs. on Rm, LNCS 7389(ICIC2012 ), pp. 103-111, 2012(EI/ISTP).
34. 董银丽,周水生,高艳.新的软间隔 AdaBoost弱分类器权重调整算法,计算机工程,2012,38(7):125-127.
33. Shuisheng Zhou, Manfred K. Warmuth, Yinli Dong and Feng Ye. New Combination Coefficients for AdaBoost Algorithms, ICNC 2010, pp:3194-3198(EI/ISTP).
32. Jiangtao Cui, Zhiyong An, Yong Guo, Shuisheng Zhou. Efficient nearest neighbor query based on extended B-tree in high-dimensional space. Pattern Recognition Letters, 2010, 31(12):1740-1748SCI/EI).
31. Shuisheng Zhou, Hongwei Liu, Feng Ye. Variant of Gaussian Kernel and Parameter Setting Method for Nonlinear SVM. Neurocomputing, 2009, 72(13-15):2931-2937(SCI/EI).
30. Shuisheng Zhou, Hongwei Liu, Lihua Zhou. A New Iterative Algorithm Training SVM. Optimization Method and Software,2009,24(6): 913-932 (SCI/EI).
29. Tiantian Chang, Hongwei Liu, Shuisheng Zhou. Large scale classification with local diversity AdaBoost SVM algorithm, JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 20(6):1344-1350, 2009/12(SCI/EI).
28. 赵玲玲,周水生, 王雪岩. 基于集成算法的半监督学习, 信号处理, 2009, 25(8A):320-323.
27. Feng Ye, Hongwei Liu, Shuisheng Zhou, Sanyang Liu. A smoothing trust-region Newton-CG method for minimax problem. Applied Mathematics And Computation, 2008, 199(2):581-589. (SCI/EI).
26. B. S. Goh, Feng Ye, Shuisheng Zhou. Steepest Descent Algorithms in Optimization with Good Convergence Properties, 20th Chinese Control and Decision Conference, 2008/7/2, pp 1526-1530.(EI/ISTP)
25. Shuisheng Zhou, Hongwei Liu, Lihua Zhou. Semismooth Newton Support Vector Machine. Pattern Recognition Letters, 2007, 28(15): 2054-2062. (SCI/EI).
24. Jiangtao Cui, Shuisheng Zhou, Junding Sun. Efficient high-dimensional indexing by sorting principal component. Pattern Recognition Letters. 2007, 28(16): 2412-2418.(SCI/EI).
23. Jiangtao Cui, Shuisheng Zhou, Shan Zhao. PCR-tree: A Compression-based index structure for similarity searching in high-dimensional image databases, FSKD 2007, pp 395-400, 2007/8/24 (EI/ISTP) .
22. Shuisheng Zhou, Hongwei Liu, Feng Ye. The Variant of Gaussian Kernel and Its Model Selection Method, 3ed international conference on Natural Computation, Haikou, China, 2007, August, pp683-687.( EI/ISTP).
21. 王钰,周水生, 刘红卫. 采用双目标优化的核参数选择方法, 电光与控制, 2007, 14(06):197-201.
20. Shuisheng Zhou, Hongwei Liu, Jiangtao Cui, Lihua Zhou. Exact Semismooth Newton SVM. SLNSC 4221: Advance in Natural Computation,2006, 9(SCI/EI/ISTP).
19. Shuisheng Zhou, Weiwei Wang, Lihua Zhou. A New Technique for Generalized Learning Vector Quantization Algorithm. Image and Vision Computing, 2006, Vo.24, No. 7, 649-655 (SCI/EI).
18. 周水生, 周利华. 共轭梯度型支撑向量机(CGSVM). 模式识别与人工智能, 2006, 19,2,129-136. (EI)
17. 周水生, 詹海生, 周利华. 训练支持向量机的Huber近似算法. 计算机学报, 2005, 28, 10, 1664-1670.(EI)
16. 周水生, 周利华. 训练支持向量机的低维Newton算法, 系统工程与电子技术, 2004, 26, 9, 1315-1318. (EI)
15. 张惠娟, 周水生, 周利华. 一种混合实时任务系统的公平调度算法. 西安电子科技大学学报, 2004, 31, 2, 272-275. (EI)
14. Shuisheng Zhou, Lihua Zhou. A new measure to improve the performance of the LVQ algorithms, Picture Coding Symposium. Saint Malo, France, 2003, 4, 115-118. (EI).
13. 周水生,容晓锋,周利华, 训练支持向量机的极大熵方法. 信号处理, 2003,19, 6, 595-599.
12. 周水生, 张惠娟, 崔江涛, 周利华.一种提高学习向量量化算法的新方法. 中国图像图形学报. 2003, 8, A, 59-63.
11. 周水生, 周利华. 修正的广义学习向量量化算法. 计算机工程, 2003, 29, 13, 34-36. (EI)
10. 周水生, 容晓峰, 周利华. 计算两个凸多面体间距离的一个新算法. 苏州科技学院学报. 2003,20,2, 11-16.
9. 崔江涛, 周水生, 周利华. 高维图像数据库中一种新的多分辨率特征匹配算法. 中国图像图形学报. 2003, 8, A, 488-491.
8. Shuisheng Zhou, Lihua Zhou, Weiguang Liu, A new generalized learning vector quantization algorithm. SPIE 2002, Vol 4875: 111-117. (EI, ISTP).
7. 周水生，周利华. 确定最优分类超平面的新算法. 西安电子科技大学学报. 2002, 29, 6, 791-795. (EI)
6. 周水生, 容晓峰, 周利华. 判断两个凸多面体相交的简单算法. 宝鸡文理学院学报, 2002, 22, 1, 24-26.
5. 赵天绪, 郝跃，周水生. VLSI冗余单元最优分配的遗传算法. 电子与信息学报. 2001, 23, 1, 96-99.
4. 刘红英; 刘三阳; 周水生. 两层广义线性规划. 系统工程学报. 2000, 15,2, 131-135.
3. 周水生,刘三阳,刘红英.价格控制问题及其推广形式的罚函数法. 系统工程学报, 1999,14,2,156-161.
2. 周水生, 刘三阳. 价格控制问题的基本性质. 应用数学与计算数学学报. 1998,12,2,53-58.
1. 周水生, 刘三阳. 线性-二次二层规划问题的性质及全局算法. 西安电子科技大学学报,1998,25, 1, 24-27.