学习经历 2004-2007 河海大学，模式识别与智能系统专业， 硕士； 2010-2011 河海大学，计算机应用技术专业， 博士。 工作经历： 2011至今 南京信息工程大学计算机与软件学院， 教师。

人工神经网络、机器学习、模式识别、数据挖掘等

[1] Shuiming Zhong, Yu Xue, Yunhao Jiang, et al: A Sensitivity-Based Improving Learning for Madaline Rule II. Mathematical problems in Engineering, 2014:1-8, (2014). SCIE.

[2] Yu Xue, Shuiming Zhong, Yi Zhuang, et al: An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization. Applied Mathematics and Computation, 231: 329-346, (2014). SCIE.

[3] Yinhua Lu, Tinghuai Ma, Shuiming Zhong, Jie Cao, et al. Improved locality-sensitive hashing method for approximate nearest neighbor problem. Chin. Phys. B, 23(8) (2014) SCI.

[4] Lihong Huang, Xiaoqin Zeng, Shuiming Zhong, Lixin Han: Sensitivity study of Binary Feedforward Neural Networks. Neurocomputing, 136: 268-280, (2014). SCIE.

[5] 蒋云昊, 陈炜峰, 钟水明等:干扰对消系统的非零带宽性能与延时匹配. 通信学报, 35 (7) :113-121, (2014).EI.

[6] Yan Xu, Xiaoqin Zeng, Shuiming Zhong: A New Supervised Learning Algorithm for Spiking Neurons. Neural Computation, 25(6): 1472-1511 (2013) SCI.

[7] Jing Yang, Xiaoqin Zeng, Shuiming Zhong, Shengli Wu: Effective Neural Network Ensemble Approach for Improving Generalization Performance. IEEE Trans. Neural Netw. Learning Syst., 24(6): 878-887, (2013). SCI.

[8] Jing Yang, Xiaoqin Zeng, Shuiming Zhong: Computation of multilayer perceptron sensitivity to input perturbation. Neurocomputing, 99: 390-398 (2013) SCIE.

[9] Shuiming Zhong, Xiaoqin Zeng, Shengli Wu, Lixin Han: Sensitivity-Based Adaptive Learning Rules for Binary Feedforward Neural Networks. IEEE Trans. Neural Netw. Learning Syst., 23(3): 480-491 (2012) SCI.

[10] 钟水明, 曾晓勤, 刘惠义, 徐彦: 基于离散随机技术的Madaline敏感性近似计算研究. 中国科学F辑：信息科学, 41(2):157-172 (2011)

[11] Shuiming Zhong, Xiaoqin Zeng, Huiyi Liu, Yan Xu: Approximate computation of Madaline sensitivity based on discrete stochastic technique. SCIENCE CHINA Information Sciences 53(12): 2399-2414 (2010) SCI.

[12] Xianming Chen, Xiaoqin Zeng, Rong Chu, Shuiming Zhong: A quantified sensitivity measure of Radial Basis Function Neural Networks to input variation. IJCNN 2010: 1-6.EI.

[13] Xiaoqin Zeng, Jing Shao, Yingfeng Wang, Shuiming Zhong: A sensitivity-based approach for pruning architecture of Madalines. Neural Computing and Applications 18(8): 957-965 (2009) SCIE

[14] Yan Jun Liu, Xiaoqin Zeng, Shuiming Zhong, Shengli Wu: A Sensitivity-Based Training Algorithm with Architecture Adjusting for Madalines. SMC 2009: 4586-4591.EI.

[15] 王炳辉, 曾晓勤, 钟水明. Adaline对权扰动敏感性的近似计算. 模式识别与人工智能, 2009, 22(3): 354-359.EI.

[16] Lei Lu, Xiaoqin Zeng, Shengli Wu, Shuiming Zhong: A Novel Ensemble Approach for Improving Generalization Ability of Neural Networks. IDEAL 2008: 164-171.EI.。

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