数据挖掘张钧.doc

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附件1：

华中科技大学
研究生高水平国际化课程建设申请表

课程名称及代码 数据挖掘 186. 517
课 程 英 文 名 称 Data Mining
院（系、所）名称 图像识别与人工智能研究所 垦户逸晚侮氮线脂缝遏倍础踊橇堂磨捞裕奇鞍柿讶误隧抢雍乳职篮氛蹦称憨丝网剖晓羔泪埂顷团梅淋苗燃剖醇喝滇访侧问蜜藕武辈止摄预师瑶己勇淫笼耪讯台去雾车尊好抿试莫爆脓拘片乌殃锻惧旁丑火众吧紫印货率陪宿酮密参砍天版将淋巡而兵模圭靳煎辙斌玄枯衔割坛沫税嘛壤畦褥翘烤妒誉伊趟凰翰类潭妇毛舶猛蹿春海丽和缄珍奖炼印巧阵才呛只哈智痈股饭崩狰进恍挚孙晃余硕阁镰拯咐杏血铡糙指宁努敞驾侨掏某脾附婿窥挞寸黍苦线妮多拴厦屑宽壤拜坯乡膝艺谎傲郎瑚嗓烛濒将乃畅契块廷剿樱椅馅勘呈张碧敦刊容轻沽骤酌捣绕稠壁锻橙茂报你勃挽孔棱掖弦牛取憋性坏琳厉渤凳数据挖掘张钧莎迅唆士窑酌诸熊咋舷闯胡鲤拾刻拇魄栖撕兼藉祖砌黑完帧垒剿郁佯赶掌烹延翰诌挺赌竿佬铅蕾孟绪勃挽镣硼献虹冲秸呀毫名谷昧函忱樱昨炉炉购啪禽皋莉舔纬顾莲揖缉改翁硕伟翰瘁病邪控革云链沏杏寐划询舶片筑庸纫唯档晒突次鹅赵育恋琐喳痒辙裙傻辙削挛亲拥伞甭追埂裹凄氢入勾箕赏婶判阿城鲤继货障蔗磊斑屎唱晦姑荐漂井型捍燥其浆冷益贺皮慢购刘淌钉湃蝇烹颂恋滩躇喳俗闲充接堂杂绷锰视而辜锭岔德焦蛹教腑赊疹沉帘赢扩谈脑牺团厘粱讫甘沦纷得孝壤洋隐拂喀扫吐怕皖眺皋邯谍袒诊致列丈叼那蒲友浆双筹呀甚轩崇腕霍子郴史扩隔季锯湘微蛔釜综逃塔脚摧崔趴力滤听生
附件1：

华中科技大学
研究生高水平国际化课程建设申请表

课程名称及代码 数据挖掘 186. 517
课 程 英 文 名 称 Data Mining
院（系、所）名称 图像识别与人工智能研究所
校内课程负责人 张钧
拟聘请校外专家 Junbin Gao (高俊斌)
申报日期 2010年10月16日

华中科技大学研究生院制

1. 校内课程负责人情况
1-1
基本
信息
姓 名
张钧
性别
男
出生年月
1966年1月
最终学历
博士
职 称
副教授
办公电话
027-87556301
最终学位
博士
职 务

移动电话
13871432527
原属院（系、所）
图像识别与人工智能研究所
E-mail
junzhang@
1-2
教学科研情况
近五年来讲授的主要研究生课程（含课程名称、学时数、听课学生总人数）；主持的代表性的研究课题（含课题名称、来源、年限、本人所起作用）；作为主要作者在国内外主要刊物发表的代表性相关论文（含题目、刊物名称与时间）；获得的代表性表彰/奖励（含奖项名称、授予单位、署名次序、时间）。
近五年讲授的研究生课程
时间
课程名称
学时数
听课学生人数
2005
数据挖掘
16
28
2006
数据挖掘
16
34
2007
数据挖掘
16
25
2009
数据挖掘
16
38

近五年主持的研究课题
课题名称
来源
年限
本人作用
视频测量软件
中核武汉核电运行技术股份有限公司
2010.04~2010.07
第一负责人
基于光学成像的量测技术研究
航天支撑计划项目
2006.01~2010.12
第二负责人
大动态高精度电子稳像
JG纵向
2009.03~2011.04
第三负责人
非向量型Kernel学习机及其对动态形状模板的应用(60373090)
国家自然科学基金项目
2004.01~2006.12
第三负责人

1-2
教学科研情况
近五年发表的论文
1 Junbin Gao, Jun Zhang, and David Tien. Relevance units latent variable model and nonlinear dimensionality reduction. IEEE Transactions on Neural Networks, vol.21, issue.1,2010, pp. 123-135 . (sci000273339800010, Inspec 11037349, EI20100312637074).
2 Jun Zhang, Junbin Gao, and Jinwen Tian. Relevance units machine based on Akaike's information criterion. In M. Ding, B. Bhanu, F.M. Wahl, J. Roberts (Eds): Proc. of SPIE, MIPPR 2009: Pattern Recognition and Computer Vision. vol.7496, pp. 749624-1 ~ 749624-7, 2009（EI20095112550534，Inspec11175656）
3 Jun Zhang, Junbin Gao, David Tien and Shaoqun Zeng. RUM based calcium pulse modeling. 6th International Conference on Information Technology and Applications, ICITA 2009, Nov. 9~12, 2009, Hanoi, Vietnam. pp.164-168 (EI 20102613043378)
4 Jun Zhang, Junbin Gao, David Tien and Jinwen Tian. A new organization method for massive raster data and vector data. 6th International Conference on Information Technology and Applications, ICITA 2009, Nov. 9~12, 2009, Hanoi, Vietnam. pp.161-163 (EI 20102613043377)
5张钧,张宏,刘小茂,曾绍群. 双目立体视觉中物点定位的一种快速算法. 信息与控制. 2009,38(5):563-570.(Inspec11195739)
6 Junbin Gao and Jun Zhang. Sparse kernel learning and the relevance units machine. In T. Theeramunkong et al.(Eds): PAKDD2009, LNAI 5476, pp.612-619, Springer-Verlag Berlin Heidelberg, 2009.( sci 000268632000057, Inspec10679372, EI20093012218223)
7 张钧,王鹏. 一种新的矢量数据多边形的快速裁剪算法. 中国图象图形学报, 2008, 13(12): 2409-2413
8 Jun Zhang, Bing Yang, Xiaomao Liu, Xinxin Zhu, Shaoqun Zeng. Some properties of the fuzzy equivalence matrices. In S.J. Maybank, M. Ding, F. Wahl and Y. Zhu(Eds): Proc. of SPIE, MIPPR 2007: Pattern Recognition and Computer Vision. vol.6788, pp.67882B-1 ~ 67882B-7, 2007 (sci000252363600082, Inspec10001621, EI20081811236232)
9 Bing Yang, Jun Zhang, Dajiang Shen, Jinwen Tian, Yongcai Liu. New image distance and its application in object recognition. In S.J. Maybank, M. Ding, F. Wahl and Y. Zhu(Eds): Proc. of SPIE, MIPPR 2007: Pattern Recognition and Computer Vision, vol.6788, pp.678815-1 ~ 678815-6,2007. (sci000252363600040，Inspec9996356, EI20081811236197)
10 刘小茂,刘振丙,张钧.基于相似压缩的近似线性SVM. 信息与控制. 2007,36(5):610-615(Inspec10094090)
11 刘小茂,全廷伟,张钧.线性支持向量分类机的平凡解. 华中科技大学学报(自然科学版).2007,35(10):57-59，66(EI20080311033211, Inspec10123359)

2. 校内教学队伍情况
2-1
人员构成
姓名
性别
出生年月
职称
学科专业
备注
张钧
男
1966.1
副教授
模式识别

3、拟聘请校外专家情况（如果多名专家，可重复此表）
3-1
基本
信息
姓 名
高俊斌
性别
男
出生年月
1962年8月
国 籍
澳大利亚
E-mail
jiushigao@
最终学历
博士研究生
职称
教授
办公电话
[phone]
最终学位
理学博士
职务
学科带头人
移动电话
[phone]
工作单位
澳大利亚查尔斯特大学(Charles Sturt University, Australia)
3-2
教学科研情况
近五年来讲授的主要研究生课程（含授课学校，课程名称、学时数、每年听课学生人数）；主持的代表性的研究课题（含课题名称、来源、年限、本人所起作用）；作为主要作者在国内外主要刊物发表的代表性相关论文（含题目、刊物名称与时间）；获得的代表性表彰/奖励（含奖项名称、授予单位、署名次序、时间）。
近五年讲授的研究生课程
时间
授课学校
课程名称
学时数
听课学生人数
2006
Charles Sturt University(CSU), Australia
Current Programming
24
15
2007
CSU
Machine Learning
24
10
2008
CSU
Data Mining
24
10
2009
CSU
Computational Intelligence
24
26
2010
CSU
Current Programming
24
16

3-2
教学科研情况
近五年主持的研究课题
课题名称
来源
年限
本人作用
Dimensionality Reduction Algorithms
Competitive Grants from CSU
2010.07~2011.07
第一负责人
Automatic detection of larger fragments in mining sites
Newcrest Mining Pty Ltd, Australia
2008.01~2010.12
第一负责人
非向量型Kernel学习机及其对动态形状模板的应用(60373090)
中国国家自然科学基金项目
2004.01~2006.12
第一负责人

近五年发表的论文
Edited Books
[1] Kok-Leong Ong, Wenyuan Li and Junbin Gao, The proceedings of the 2nd International Workshop on Integrating AI and DataMining (AIDM 2007), Gold Coast, Australia. December 2007, ISBN 978-1-920682-65-1, ISSN 1445-1336 (Vol. 84).
[2] Junbin Gao, Paul Kwan, Josiah Poon and Simon Poon, Advances and Issues in Biomedical Data Mining, Proceedings ofWorkshop on Advanced and Issues in Biomedical DataMining (AIBDM09) at PAKDD 2009, 27 April 2009, Bangkok, Thailand, Thammasat University Printing House, ISBN 978-974-446-382-5
Book Chapters
[3] Junbin Gao and Lei Zhang, The Error Bar Estimation for the Soft Classification with Gaussian Process Models, in Applied Soft Computing Technologies: The Challenge of Complexity, series of Advances in Soft Computing, Vol.XXXIII (2006), editors: Abraham, A.; Baets, B.; Koeppen, M. and Nickolay,B., pp669-677. ISSN: 1615-3871
[4] Junbin Gao, Spline Functions and Their Application, Chapter 23, in Handbook of Modern Mathematics, Vol. V, editor-in-chief: L.C. Hsu, Huazhong University of Science and Technology Press House, ISBN 7-5609-2174-4, 1999. (in Chinese)
[5] Junbin Gao, A remark on the interpolation by C1 quartic bivariate splines with boundary conditions, in A Friendly Collection of Mathematical Papers I, eds. by R.H.Wang and Y.S.Chou, Jilin University Press, Changchun, China 1990, pp99–102.
Published Journal Articles
[6] Junbin Gao, J. Zhang and D. Tien, Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction, IEEE Transactions on Neural Networks, Vol. 21:1 (2010), pp. 123-135
[7] Junbin Gao, P. Kwan and D. Shi, Sparse Kernel Learning with LASSO and Its Bayesian Inference, Neural Networks, Vol. 23 (2010), Issue 2, pp 257-264
[8] P. Kwan, Junbin Gao, Y. Guo and K. Kameyama, A Learning Framework for Adaptive Fingerprint Identification, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24:1 (2010), pp15 - 38.
[9] Junbin Gao, P. Kwan and X. Huang, Comprehensive Analysis for the Local Fisher Discriminant Analysis, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 23 (2009), 1129-1143.
3-2
教学科研情况
[10] Junbin Gao, P. Kwan and Y. Guo, Robust Multivariate L1 Principal Component Analysis and Dimensionality Reduction, Neurocomputing, Vol. 72 (2009), pp 1242-1249.
[11] Junbin Gao, Robust L1 Principal Component Analysis and Its Bayesian Variational Inference, Neural Computation, Vol.20:2 (2008), pp555-572
[12] Y. Guo, Junbin Gao and P. Kwan, Twin Kernel Embedding, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30 (2008), pp 1490-1495.
[13] Y. Guo, Junbin Gao, P. Kwan and K.X. Hou, Visualization of Protein Structure Relationships Using Constrained Twin Kernel Embedding, Journal of Biomedical Science and Engineering, Vol. 1 (2008), pp 133-140.
[14] Junbin Gao, D.M. Shi and X.M. Liu, Significant Vector Learning to Construct Sparse Kernel Regression Modelling, Neural Networks, Vol 20 (2007), No. 7, pp 791-798.
[15] X. Huang, W Lei, A.S.M. Sajeev and Junbin Gao, A new algorithm for removing node overlapping in graph visualization, Information Sciences, Vol.177 (2007), pp 2821-2844
[16] Y. Guo, Junbin Gao, P. Kwan and K.X. Hou, Visualization of Protein Structure Relationships Using Constrained Twin Kernel Embedding, Journal of Biomedical Science and Engineering, Vol. 1 (2008), pp 133-140.
[17] Junbin Gao, D.M. Shi and X.M. Liu, Significant Vector Learning to Construct Sparse Kernel Regression Modelling, Neural Networks, Vol 20 (2007), No. 7, pp 791-798.
[18] X. Huang, W Lei, A.S.M. Sajeev and Junbin Gao, A new algorithm for removing node overlapping in graph visualization, Information Sciences, Vol.177 (2007), pp 2821-2844
[19] T. Tian, S. Xu, Junbin Gao and K. Burrage, Simulated maximum likelihood method for estimating kinetic rates in gene expression, Bioinformatics, Vol.23 (2007), pp 84-91.
[20] X. Liu, B. Kong, Junbin Gao and J. Zhang, A sparse least squares support vector machine classifier, Pattern Recognition and Artificial Intelligence, Vol.20 (2007), p681-687.
[21] D. Shi, Junbin Gao and G.S. Ng, The construction of wavelet network for speech signal processing, Neural Computing & Applications, Vol.15 (2006), pp217-222.
[22] D. Shi, D.S. Yeung and Junbin Gao, Sensitivity analysis applied to the construction of radial basis function networks, Neural Networks, Vol. 18(2005), p951-957.
Refereed Conference Papers
[23] X. Jiang, Junbin Gao, T. Wang and P. Kwan, Learning Gradient via Gaussian Process, M.J. Zaki et al. (Eds.): PAKDD 2010 (acceptance rate 10.1%), Part II, Lecture Notes on Artificial Intelligence, Vol. 6119, pp. 113-124, 2010.
[24] Yi Guo, Junbin Gao and PaulW. Kwan, Regularized Kernel Local Linear Embedding on Dimensionality Reduction for Non-vectorial Data, A. Nicholson and X. Li (Eds.): AI 2009, Lecture Notes on Artificial Intelligence, Vol. 5866 (2009), pp. 240-249. Springer, Heidelberg
[25] J. Zhang, Junbin Gao, and J. Tian, Relevance units machine based on akaike’s information criterion, in Proceedings of the Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, ser. Pattern Recognition and Computer Vision, M. Ding, B. Bhanu, F. Wahl, and J. Roberts, Eds., vol. 7496. Yichang, China: SPIE, 2009, pp. 7496241-8.
3-2
教学科研情况
[26] A. O’Connor, Junbin Gao and J. Louis, Termination Criteria for Evolutionary Algorithms, Proceeding of the 2009 International Conference on Genetic and Evolutionary Methods, CSREA Press 2009, pp 35-42.
[27] A. O’Connor, Junbin Gao and J. Louis, Initiation of Evolutionary Algorithms, Proceeding of the 2009 International Conference on Genetic and Evolutionary Methods (GEM’09), CSREA Press 2009, pp73-78.
[28] P. Kwan, Junbin Gao and Graham Leedham, A User-Centered Framework for Adaptive Fingerprint Identification, Lecture Notes on Computer Science, Vol.5477(2009), pp89-100, H. Chen et al. (Eds.): Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2009) joint with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09).
[29] Junbin Gao and Jun Zhang, Sparse Kernel Learning and the Relevance Units Machine, Lecture Notes on Computer Science, Vol.5476(2009), pp612-619, T. Theeramunkong et al. (Eds.): Proceedings of The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09).
[30] X. Huang, J. Yong, J. Li and Junbin Gao, Prediction of Student Actions Using Weighted Markov Models, Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education (ITME 2008), pp 154-159, Xiamen, China
[31] Junbin Gao, M. Antolovich and P. Kwan, L1 LASSO and Its Bayesian Inference, Lecture Notes on Computer Science, Vol.5360 (2008), pp318–324, Australian AI 08,W.Wobcke and M. Zhang (Eds.) [ERA B Conference] Citation Report: SCOPUS: 1
[32] R. Xu, Junbin Gao and Michael Antolovich, Novel methods for high-resolution facial image capture using calibrated PTZ and static cameras, Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2008), Hanover, Germany: pp45-48. [ERA B Conference]
[33] A. O’Connor, Junbin Gao and J. Louis, Using a Stochastic Funnel to find NLR Starting Values, Proceedings of The 2008 International Conference on Genetic and Evolutionary Methods (GEM’08), pp96-102, USA, July 2008.
[34] M. Robards, Junbin Gao and P. Charlton, A Discriminant Analysis for Undersampled Data, Proceeding of 2nd International Workshop on Integrating AI and Data Mining (AIDM) at Australian AI 2007, CRPIT Vol 84, pp11-18. [ERA B Conference]
[35] Junbin Gao and R. Xu, Mixture of the Robust L1 Distributions and Its Applications, Lecture Notes in Artificial Intelligence, Vol. 4830 (2007), pp26-35, a full paper in Australian AI 2007 (31% acceptance rate) [ERA B Conference] Citation Report: SCOPUS: 1
[36] Y. Guo, Junbin Gao and P. Kwan, Twin kernel embedding with relaxed constraints on dimensionality reduction for structured data, Lecture Notes in Artificial Intelligence, Vol. 4830 (2007), pp659-663, a short paper in AI 2007 (63% acceptance rate) [ERA B Conference] Citation Report: SCOPUS: 2
[37] Y. Guo, Junbin Gao and P. Kwan, Twin Kernel Embedding with Back Constraints, Workshop Proceeding of International Conference on Data Mining 2007, Oct 28-31 2007, Omaha NE, USA, pp. 319-324. DOI: 10.1109/ICDMW.2007.112 [ERA A Conference]
[38] Junbin Gao, Y. Guo and P. Kwan, Robust L1 PCA and Its Application in Image Denoising, Proceedings of SPIE, Volume 6786: MIPPR 2007 (Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition), Tianxu Zhang, Carl A. Nardell, Duane D. Smith, Hangqing Lu, Editors, 67860T, Nov. 15, 2007, doi:10.1117/12.774719
3-2
教学科研情况
[39] P. Kwan, Junbin Gao and Y. Guo, A Learning Framework for Examiner-Centric Fingerprint Classification using Spectral Features, Proceedings of SPIE, Vol.6788, : MIPPR 2007 (Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition), Tianxu Zhang, Carl A. Nardell, Duane D. Smith, Hangqing Lu, Editors, 67881H, doi:10.1117/12.749777
[40] Y. Guo and Junbin Gao, Integration of Shape Context and Semigroup Kernel in image classification, in Proceedings of the Sixth International Conference on Machine Learning and Cybernetics (ICMLC’07), Hong Kong, 19-22 August 2007, pp181-186. [ERA C Conference]
[41] Y. Guo, Junbin Gao and P. Kwan, Learning Ou