博士，教授，博导，信息管理系主任，IEEE会员，中国计算机学会高级会员, 中国人工智能学会机器学习专业委员会委员,中国人工智能学会粗糙集与软计算专委会委员，中国计算机学会人工智能与模式识别专业委员会委员，江苏省计算机学会第七届理事会理事，江苏省计算机学会第七届理事会理事青年工作委员会副主任。1997年在西安电子科技大学获得工学学士学位；2002年，在西安电子科技大学获得工学博士学位，博士论文被评选为陕西省优秀博士学位论文。2003年4月至2005年5月，在上海交通大学控制科学与工程博士后流动站工作。2005年5月至2010年8月，在西安电子科技大学智能信息处理研究所作研究工作。其间，从2010年1月至2010年4月在台湾元智大学担任客座副教授。从2010年8月至今，在苏州大学计算机科学与技术学院工作，2015年入选苏州大学“东吴学者计划”。
主要从事机器学习、模式识别、图像处理方面的研究。为《IEEE Transactions on Pattern Recognition and Machine Intelligence 》、《IEEE Transactions on Neural Networks》、《Arabian Journal for Science and Engineering》、《模式识别与人工智能》等学术期刊及国际学术会议的审稿人。到目前为止与合作者出版专著3部，发表论文100余篇，其中SCI检索30余篇,EI检索60余篇，SCI他引400余次；获发明专利10余项，获国家自然科学奖二等奖、教育部高等学校科学研究优秀成果自然科学一等奖、陕西省科技进步一等奖、江苏省科技进步二等奖和三等奖、以及西安市科技进步一等奖各一项；作为项目负责人，申请到国家自然科学基金三项、省自然科学基金两项。获得江苏省杰出青年基金资助，是江苏省高校“青蓝工程”优秀青年骨干教师培养对象，并获得江苏省首届“江苏省优秀计算机科技工作者” 称号，及苏州市首届“青年计算机科技优秀人才”称号。
本科生：《数据仓库与数据挖掘》
硕士生：《机器学习》
主要的国际期刊论文列表
Zhao Zhang*, Yan Zhang, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan. Discriminative Sparse Flexible Manifold Embedding with Novel Graph for Robust Visual Representation and Label Propagation. Pattern Recognition (PR), 2017, 61: 492–510.
Li Zhang*, Wei-Da Zhou. Fisher-regularized support vector machine. Information Sciences, 2016, 343-344(5): 79-93.
Wenxuan Xu, Li Zhang*, Yaping Lu, SD-MSAEs: Promoter recognition in human genome based on deep feature extraction, Journal of Biomedical Informatics, 2016, 61 (3): 55–62.
Mei Lu*, Xiang-Jun Zhao, Li Zhang, Fan-Zhang Li, Semi-supervised concept factorization for document clustering. Information Sciences, 2016, 331(2): 86-98.
Li Zhang*, Liqiang Qian, Chuntao Ding, Weida Zhou, Fanzhang Li. Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data, Computers in Biology and Medicine, 2015, 64(9): 236-245.
Li Zhang*，Yiqin Leng, Jiwen Yang, Fanzhang. Supervised locally linear embedding algorithm based on orthogonal matching pursuit. IET Image Processing, 2015, 9(8): 626-633.
Peipei Xia, Li Zhang*, Fanzhang Li. Learning similarity with cosine similarity ensemble. Information Sciences. 2015, 307(6): 39–52.
Chuntao Ding, Li Zhang*, Double adjacency graphs-based discriminant neighborhood embedding, Pattern Recognition, 2015, 48(5): 1734–1742.
Li Zhang*, Wei-Da Zhou, Time series prediction using sparse regression ensemble based on l2-l1 problem, Soft Computing, 2015, 19(3): 781-792.
Jin Cao, Li Zhang*, Bangjun Wang, Fanzhang Li, Jiwen Yang, A fast gene selection method for multi-cancer classification using multiple support vector data description, Journal of Biomedical Informatics, 2015, 53(2): 381-389.
Yiqin Leng, Li Zhang*, Jiwen Yang. Orthogonal matching pursuit-based incremental locally linear embedding algorithm, International Journal Autonomous and Adaptive Communications Systems, 2015, 8(2-3): 257-267.
L. Zhang, W. D Zhou, G. R. Chen, Y.P. Lu, F. Z Li. Sparse signal reconstruction using decomposition algorithm, Knowledge-Based Systems, 2013, 54(18), 172-179.
L. Zhang, and W. D. Zhou. A fastalgorithm for kernel 1-norm support vector machines, Knowledge-Based Systems,2013, 52(16), 223 – 235.
L. Zhang, and W. D. Zhou. 1-normsupport vector novelty detection and its sparseness, Neural Networks, 2013, 48(12),125-136.
L. Zhang, and W. D. Zhou. Analysisof programming properties and the row–column generation method for 1-normsupport vector machines, Neural Networks,2013, 48(12), 32-43
L. Zhang, W.-D. Zhou, P.-C. Chang,Ji-Wen Yang and Fan-Zhang Li. Iterated time series prediction with multiplesupport vector regression models, Neurocomputing,2013, 99, 411–422
W. Zhong, J. Liu, L. Zhang.Evolutionary dynamics of continuous strategy games on graphs and socialnetworks under weak selection, BioSystems, 2013, 111, 102– 110.
D. Wang, P.-C. Chang, L.Zhang, J.-L. Wu, C. L. Zhou. The stability analysis for a novel feedbackneural network with partial connection, Neurocomputing, 2013, 116, 22-29
L. Zhang, W.-D. Zhou, P.-C. Chang, et al. Kernel sparserepresentation-based classifier, IEEE Transactionson Signal Processing, 2012, 60, 1684-1695.
Li Zhang and Weida Zhou. Sparse ensembles using weightedcombination methods based on linear programming. Pattern Recognition, 44(1):97-106,January 2011.
Li Zhang and Weida Zhou. Density-induced margin supportvector machines. Pattern Recognition, 44(7):1448 – 1460, July 2011.
Li Zhang, Wei-Da Zhou, and Pai-Chann Chang. Generalizednonlinear discriminant analysis and its small sample size problems.Neurocomputing, 74(4):568–574, January 2011.
Li Zhang and Weida Zhou. On the sparseness of 1-normsupport vector machines. Neural Networks, 23:373–385, April 2010.
Li Zhang, Weida Zhou, and Licheng Jiao. Complex-valuedsupport vector classifiers. Digital Signal Processing, 20:944–955, May 2010.
Li Zhang, Yugeng Xi, and Weida Zhou. Identification andcontrol of discrete-time nonlinear systems using affine support vector machines.International Journal on Artificial Intelligence Tools, 18(6):929–947, 2009.
Li Zhang, Weida Zhou, Tiantian Su, and Licheng Jiao.Decision tree support vector machine. International Journal on ArtificialIntelligence Tools, 16(1):1–16, 2007.
Li Zhang, Weida Zhou, and Licheng Jiao. Wavelet supportvector machine. IEEE Trans. SMC Part B, 34(1):34–39, 2004.
Li Zhang, Weida Zhou, and Licheng Jiao. Hidden spacesupport vector machines. IEEE Trans. NNs, 15(6):1424–1434, 2004.
招收博士研究生
招收硕士研究生
招收有意科研的本科生
博士，教授，博导，信息管理系主任，IEEE会员，中国计算机学会高级会员, 中国人工智能学会机器学习专业委员会委员,中国人工智能学会粗糙集与软计算专委会委员，中国计算机学会人工智能与模式识别专业委员会委员，江苏省计算机学会第七届理事会理事，江苏省计算机学会第七届理事会理事青年工作委员会副主任。1997年在西安电子科技大学获得工学学士学位；2002年，在西安电子科技大学获得工学博士学位，博士论文被评选为陕西省优秀博士学位论文。2003年4月至2005年5月，在上海交通大学控制科学与工程博士后流动站工作。2005年5月至2010年8月，在西安电子科技大学智能信息处理研究所作研究工作。其间，从2010年1月至2010年4月在台湾元智大学担任客座副教授。从2010年8月至今，在苏州大学计算机科学与技术学院工作，2015年入选苏州大学“东吴学者计划”。
主要从事机器学习、模式识别、图像处理方面的研究。为《IEEE Transactions on Pattern Recognition and Machine Intelligence 》、《IEEE Transactions on Neural Networks》、《Arabian Journal for Science and Engineering》、《模式识别与人工智能》等学术期刊及国际学术会议的审稿人。到目前为止与合作者出版专著3部，发表论文100余篇，其中SCI检索30余篇,EI检索60余篇，SCI他引400余次；获发明专利10余项，获国家自然科学奖二等奖、教育部高等学校科学研究优秀成果自然科学一等奖、陕西省科技进步一等奖、江苏省科技进步二等奖和三等奖、以及西安市科技进步一等奖各一项；作为项目负责人，申请到国家自然科学基金三项、省自然科学基金两项。获得江苏省杰出青年基金资助，是江苏省高校“青蓝工程”优秀青年骨干教师培养对象，并获得江苏省首届“江苏省优秀计算机科技工作者” 称号，及苏州市首届“青年计算机科技优秀人才”称号。
本科生：《数据仓库与数据挖掘》
硕士生：《机器学习》
主要的国际期刊论文列表
Zhao Zhang*, Yan Zhang, Fanzhang Li, Mingbo Zhao, Li Zhang and Shuicheng Yan. Discriminative Sparse Flexible Manifold Embedding with Novel Graph for Robust Visual Representation and Label Propagation. Pattern Recognition (PR), 2017, 61: 492–510.
Li Zhang*, Wei-Da Zhou. Fisher-regularized support vector machine. Information Sciences, 2016, 343-344(5): 79-93.
Wenxuan Xu, Li Zhang*, Yaping Lu, SD-MSAEs: Promoter recognition in human genome based on deep feature extraction, Journal of Biomedical Informatics, 2016, 61 (3): 55–62.
Mei Lu*, Xiang-Jun Zhao, Li Zhang, Fan-Zhang Li, Semi-supervised concept factorization for document clustering. Information Sciences, 2016, 331(2): 86-98.
Li Zhang*, Liqiang Qian, Chuntao Ding, Weida Zhou, Fanzhang Li. Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data, Computers in Biology and Medicine, 2015, 64(9): 236-245.
Li Zhang*，Yiqin Leng, Jiwen Yang, Fanzhang. Supervised locally linear embedding algorithm based on orthogonal matching pursuit. IET Image Processing, 2015, 9(8): 626-633.
Peipei Xia, Li Zhang*, Fanzhang Li. Learning similarity with cosine similarity ensemble. Information Sciences. 2015, 307(6): 39–52.
Chuntao Ding, Li Zhang*, Double adjacency graphs-based discriminant neighborhood embedding, Pattern Recognition, 2015, 48(5): 1734–1742.
Li Zhang*, Wei-Da Zhou, Time series prediction using sparse regression ensemble based on l2-l1 problem, Soft Computing, 2015, 19(3): 781-792.
Jin Cao, Li Zhang*, Bangjun Wang, Fanzhang Li, Jiwen Yang, A fast gene selection method for multi-cancer classification using multiple support vector data description, Journal of Biomedical Informatics, 2015, 53(2): 381-389.
Yiqin Leng, Li Zhang*, Jiwen Yang. Orthogonal matching pursuit-based incremental locally linear embedding algorithm, International Journal Autonomous and Adaptive Communications Systems, 2015, 8(2-3): 257-267.
L. Zhang, W. D Zhou, G. R. Chen, Y.P. Lu, F. Z Li. Sparse signal reconstruction using decomposition algorithm, Knowledge-Based Systems, 2013, 54(18), 172-179.
L. Zhang, and W. D. Zhou. A fastalgorithm for kernel 1-norm support vector machines, Knowledge-Based Systems,2013, 52(16), 223 – 235.
L. Zhang, and W. D. Zhou. 1-normsupport vector novelty detection and its sparseness, Neural Networks, 2013, 48(12),125-136.
L. Zhang, and W. D. Zhou. Analysisof programming properties and the row–column generation method for 1-normsupport vector machines, Neural Networks,2013, 48(12), 32-43
L. Zhang, W.-D. Zhou, P.-C. Chang,Ji-Wen Yang and Fan-Zhang Li. Iterated time series prediction with multiplesupport vector regression models, Neurocomputing,2013, 99, 411–422
W. Zhong, J. Liu, L. Zhang.Evolutionary dynamics of continuous strategy games on graphs and socialnetworks under weak selection, BioSystems, 2013, 111, 102– 110.
D. Wang, P.-C. Chang, L.Zhang, J.-L. Wu, C. L. Zhou. The stability analysis for a novel feedbackneural network with partial connection, Neurocomputing, 2013, 116, 22-29
L. Zhang, W.-D. Zhou, P.-C. Chang, et al. Kernel sparserepresentation-based classifier, IEEE Transactionson Signal Processing, 2012, 60, 1684-1695.
Li Zhang and Weida Zhou. Sparse ensembles using weightedcombination methods based on linear programming. Pattern Recognition, 44(1):97-106,January 2011.
Li Zhang and Weida Zhou. Density-induced margin supportvector machines. Pattern Recognition, 44(7):1448 – 1460, July 2011.
Li Zhang, Wei-Da Zhou, and Pai-Chann Chang. Generalizednonlinear discriminant analysis and its small sample size problems.Neurocomputing, 74(4):568–574, January 2011.
Li Zhang and Weida Zhou. On the sparseness of 1-normsupport vector machines. Neural Networks, 23:373–385, April 2010.
Li Zhang, Weida Zhou, and Licheng Jiao. Complex-valuedsupport vector classifiers. Digital Signal Processing, 20:944–955, May 2010.
Li Zhang, Yugeng Xi, and Weida Zhou. Identification andcontrol of discrete-time nonlinear systems using affine support vector machines.International Journal on Artificial Intelligence Tools, 18(6):929–947, 2009.
Li Zhang, Weida Zhou, Tiantian Su, and Licheng Jiao.Decision tree support vector machine. International Journal on ArtificialIntelligence Tools, 16(1):1–16, 2007.
Li Zhang, Weida Zhou, and Licheng Jiao. Wavelet supportvector machine. IEEE Trans. SMC Part B, 34(1):34–39, 2004.
Li Zhang, Weida Zhou, and Licheng Jiao. Hidden spacesupport vector machines. IEEE Trans. NNs, 15(6):1424–1434, 2004.
招收博士研究生
招收硕士研究生
招收有意科研的本科生