于剑

博士、教授、人工智能研究院院长,交通数据分析与挖掘北京市重点实验室主任

基本信息

办公电话:010-51688291 电子邮件: jianyu@bjtu.edu.cn
通讯地址:北京交通大学计算机学院 邮编:100044

教育背景

 

1988.9-1991.7, 北京大学数学科学学院本科

1991.9-1994.7,  北京大学数学科学学院硕士

1997.9-2000.7,北京大学数学科学学院博士

 


工作经历

2019.12-

北京交通大学人工智能研究院院长

2017.12-

北京交通大学人工智能研究院常务副院长

2016.12

二级教授

2013.5-

交通数据分析与挖掘北京市重点实验室主任

2008.11-

《北京交通大学学报》编委

2008.11-2009.5

TAMU,计算机科学系访问学者

2007.10-2017.12

北京交通大学计算机学院计算机科学系主任

2005.7-

北京交通大学计算机学院博士生导师

2004.12-

北京交通大学计算机学院教授

2004.6-2007.9

北京交通大学计算机学院计算机研究所所长

2004.3-2004.6

Queen Mary, University of London 计算机系访问学者

2002.7-2002.9

台湾新竹交通大学资讯工程系访问学者

2001.12-2004.11

北京(北方)交通大学计算机学院副教授

2000.11-2003.7

北方交通大学计算机学院计算机研究所人工智能与模式识别研究室主任

2000.7-2000.10

中国科学院声学所博士后

1998.5-2000.6

中国注册会计师, 北京兴中海会计师事务所

1994.8-1998.4

中国矿业大学北京研究生部讲师



研究方向

  • 机器学习与认知计算
  • 人工智能及应用
  • 计算机技术
  • 软件工程
  • 人工智能
  • 网络与信息安全

招生专业

  • 计算机科学与技术硕士
  • 计算机技术硕士
  • 软件工程硕士
  • 人工智能硕士
  • 计算机科学与技术博士
  • 网络与信息安全硕士
  • 计算机技术博士

科研项目

(1)  北京市自然基金重点研究专题, 弱监督学习理论研究(参加)2019-2022 200

(2)  国家重点研发计划,项目批准号:2017YFC1703506 (项目负责人)2018-2021):中医药大数据挖掘与创新应用,702

(3)  北京市科技研发专项, 图谱化深度学习技术研究及应用验证(项目负责人)2018-2019 200

(4)  国家自然科学基金项目重点项目基金,项目批准号:61632004 (项目负责人) (2017-2021): 面向认知的多源数据学习理论与算法, 265

(5)  北京科委项目,项目批准号:Z131110002813118 (项目负责人)2013-2014):基于大数据的交通计算若干问题研究, 50

(6)  国家自然科学基金项目面上基金,项目批准号:61370129 (项目负责人) (2014-2017): 基于多标记学习的网络重叠社区发现模型及应用研究, 77

(7)  教育部,“长江学者和创新团队发展计划资助No. IRT201206),参加, 10

(8)  教育部博士点基金,项目批准号:20120009110006 (项目负责人)2013-2015):融合文本信息的图像语义理解关键技术研究, 12

(9)  科技部863项目,项目批准号:2012AA040912(参与) (2012-2014)复杂装备运维服务专业化构件与系统开发, 667

(10)    国家自然科学基金重点项目,项目批准号:61033013(参与) (2011-2014): 基于认知模型的图像不变形特征理论和关键技术, 90

(11)    北京市自然科学基金项目面上基金,项目批准号:4112046 (项目负责人) (2011-2013):复杂网络聚类分析及应用, 11

(12)    国家自然科学基金重大项目面上基金,项目批准号:90820013 (项目负责人) (2009-2011): 基于相似性的认知模型与图像分析中的关键问题研究, 50

(13)    国家重大新药计划,冠心病血瘀证中药临床疗效评价关键技术研究 (2010-2011),25

(14)    中央高校基本科研业务费, 项目批准号: 2009JBZ006-1(项目负责人) (2009-2011): 智能信息感知与状态识别-机器学习,8

(15)    国家自然科学基金项目面上基金,项目批准号:60875031 (项目负责人) (2009-20011): 近邻传播算法中的几个关键问题研究, 28

(16)  973项目,项目批准号:2007CB311002 (5/16)(2007-2011):非结构化数据的数学建模与机器学习,47

(17)  2006年度教育部新世纪优秀人才支持计划,项目批准号:NCET-06-0078(项目负责人),基于统计的聚类算法的性能评估与自动选择研究(2007-2009) 50

(18)  霍英东教育基金会第十届高等院校青年教师基金项目,项目批准号:101068(项目负责人)(2006-2008) 机器学习中的教学间断现象研究, 2万美元,已经结题

(19)    教育部高等学校博士学科点专项科研基金,项目批准号:20050004008(2006-2008)(主要参加人):机器学习中的教学间断理论, 6.5万,已经结题

(20)  教育部科学技术研究重点项目,项目批准号: 02031 (2002-2003) (项目负责人): 聚类算法中的参数选择理论, 已经结题,8万

(21)    国家自然科学基金项目面上基金,项目批准号:60303014 (项目负责人) (2004-2006): 基于划分的一般聚类模型研究,已经结题(优秀),26

(22)    国家自然科学基金项目,项目批准号:60443003 (3/10) (2004-2005): 协同演化学习方法及其在数据挖掘中的应用,已经结题,14万

(23)  横向项目: 北京燃气公司统计信息系统, 2005.4-2006.12 (项目负责人),已经结题, 52万

教学工作

论文/期刊

      (1)    于剑, 图灵测试的明与暗,计算机研究与发展,57(5):906-911(2020)

(2)    Bo Liu, Liping Jing, Jia Li, Jian Yu, Alex Gittens, Michael W. Mahoney:
Group Collaborative Representation for Image Set Classification. International Journal of Computer Vision 127(2): 181-206 (2019)

(3)    Dong Deng, Liping Jing, Jian Yu, Shaolong Sun, Michael K. Ng:
Sentiment Lexicon Construction With Hierarchical Supervision Topic Model. IEEE/ACM Trans. Audio, Speech & Language Processing 27(4): 704-718 (2019)

(4)    Yafang Li, Caiyan Jia, Xiangnan Kong, Liu Yang, Jian Yu:
Locally Weighted Fusion of Structural and Attribute Information in Graph Clustering. IEEE Trans. Cybernetics 49(1): 247-260 (2019)

(5)    Jialin Hua, Jian Yu, Miin-ShenYang, Fast clustering for signed graphs based on random walk gap, Social Networks, in press (2018)

(6)    Ruisi He, Bo Ai, Andreas F. Molisch, Gordon L. Stüber, Qingyong Li, Zhangdui Zhong, Jian Yu:
Clustering Enabled Wireless Channel Modeling Using Big Data Algorithms.
IEEE Communications Magazine 56(5): 177-183 (2018)

(7)    Lixia Tian, Qizhuo Li, Chaomurilige Wang, Jian Yu:
Changes in dynamic functional connections with aging.
NeuroImage 172: 31-39 (2018)

(8)    Caiyan Jia, Matthew B. Carson, Xiaoyang Wang, Jian Yu:
Concept decompositions for short text clustering by identifying word communities.
Pattern Recognition 76: 691-703 (2018)

(9)    Bianfang Chai, Jinghong Wang, Jian Yu: A parameter selection method of the deterministic anti-annealing algorithm for network exploring. Neurocomputing 226: 192-199 (2017)

(10) Jian Yu, Chaomurilige Wang, Miin-Shen Yang:
On convergence and parameter selection of the EM and DA-EM algorithms for Gaussian mixtures.
Pattern Recognition 77: 188-203 (2018)

(11) Liu Yang, Liping Jing, Bo Liu, Jian Yu: Common latent space identification for heterogeneous co-transfer clustering. Neurocomputing 269: 29-39 (2017)

(12) Chaomurilige, Jian Yu, Miin-Shen Yang: Deterministic annealing Gustafson-Kessel fuzzy clustering algorithm. Inf. Sci. 417: 435-453 (2017)

(13) Jia Li, Chen-Yan Bai, Zhouchen Lin, Jian Yu: Automatic Design of High-Sensitivity Color Filter Arrays With Panchromatic Pixels. IEEE Trans. Image Processing 26(2): 870-883 (2017)

(14) Jia Li, Chen-Yan Bai, Zhouchen Lin, Jian Yu: Optimized Color Filter Arrays for Sparse Representation-Based Demosaicking. IEEE Trans. Image Processing 26(5): 2381-2393 (2017)

(15) Liping Jing, Chenyang Shen, Liu Yang, Jian Yu, Michael K. Ng: Multi-Label Classification by Semi-Supervised Singular Value Decomposition. IEEE Trans. Image Processing 26(10): 4612-4625 (2017)

(16) Ruisi He, Qingyong Li, Bo Ai, Yang Li-Ao Geng, Andreas F. Molisch, Vinod Kristem, Zhangdui Zhong, Jian Yu: A Kernel-Power-Density-Based Algorithm for Channel Multipath Components Clustering. IEEE Trans. Wireless Communications 16(11): 7138-7151 (2017)

(17) Bo Liu, Liping Jing, Jian Yu, Jia Li: Robust graph learning via constrained elastic-net regularization. Neurocomputing 171: 299-312 (2016)

(18) Bojun Xie, Yi Liu, Hui Zhang, Jian Yu: A novel supervised approach to learning efficient kernel descriptors for high accuracy object recognition. Neurocomputing 182: 94-101 (2016)

(19) Liu Yang, Liping Jing, Michael K. Ng, Jian Yu: A discriminative and sparse topic model for image classification and annotation. Image Vision Comput. 51: 22-35 (2016)

(20) Chen-Yan Bai, Jia Li, Zhouchen Lin, Jian Yu: Automatic Design of Color Filter Arrays in the Frequency Domain. IEEE Trans. Image Processing 25(4): 1793-1807 (2016)

(21) Liu Yang, Liping Jing, Jian Yu, Michael K. Ng: Learning Transferred Weights From Co-Occurrence Data for Heterogeneous Transfer Learning. IEEE Trans. Neural Netw. Learning Syst. 27(11): 2187-2200 (2016)

(22) 于剑,语言与图灵测试,自动化学报, 2016, 42(5): 668-669

(23) Yu J. Generalized Categorization Axioms. arXiv preprint arXiv:1503.09082, 2015.

(24) Yu J. Categorization Axioms for Clustering Results Axioms. arXiv preprint arXiv:1403.2065, 2015.

(25) Yu J. Communication: Words and Conceptual Systems . arXiv preprint arXiv:1507.08073, 2015.

(26) Chai B, Jia C, Yu J. An online expectation maximization algorithm for exploring general structure in massive networks. Physica A: Statistical Mechanics and its Applications, 2015, 438: 454-468.

(27) Li Y, Jia C, Yu J. A parameter-free community detection method based on centrality and dispersion of nodes in complex networks. Physica A: Statistical Mechanics and its Applications, 2015, 438: 321-334.

(28) Chaomurilige C, Yu J, Yang M S. Analysis of Parameter Selection for Gustafson-Kessel Fuzzy Clustering Using Jacobian Matrix,IEEE Trans. on Fuzzy System,2015,23(6),2329-2342

(29) Liu B, Jing L, Yu J, et al. Robust graph learning via constrained elastic-net regularization. Neurocomputing, 2016, 171: 299-312.

(30) Chenyan Bai, Jia Li, zhouchen Lin, Jian Yu, Yen-Wei Chen, Penrose demosaicking. IEEE Trans. on Image Processing.  VOL. 24, NO. 5, MAY 2015

(31) Zhang H, Liu Y, Xie B, Yu J. Spatially constrained sparse coding scheme for natural scene categorization. Journal of Visual Communication and Image Representation, 2015, 28: 28-35.

(32) Xie B, Liu Y, Zhang H, Yu J. Efficient image representation for object recognition via pivots selection. Frontiers of Computer Science, 2015: 1-9.

(33) Zhu J, Yu J, Wang C, et al. Object recognition via contextual color attention. Journal of Visual Communication and Image Representation, 2015, 27: 44-56.

(34) Liu Yang, Liping Jing, Jian Yu, and Michael K. Ng.  Learning transferred weights from co-occurrence data for heterogeneous transfer learning, IEEE Transactions on Neural Networks and Learning Systems, (in press).

(35) 杨柳, 于剑, 景丽萍. 一种异构直推式迁移学习算法, 软件学报, vol. 26, no. 11, pp. 2762-2780, 2015.

(36) 谢博鋆,朱杰,于剑.基于Pivots选择的有效图像块描述子.软件学报,2015,26(11):2930-2938

(37) 柴变芳,  贾彩燕, 于剑,基于概率模型的大规模网络结构发现方法,软件学报, 2014, 25(12): 2753-2766.

(38) 柴变芳, 于剑, 贾彩燕*, 一种基于随机块模型的快速广义社区发现算法, 软件学报,2013.12

(39) Jie Zhu, Jian Yu, Chaomurilige Wang et al. Colour combination attention for object recognition[J]. Image Processing, IET, 2014, 8(9): 539-547.

(40) Liyan Ma, Jian Yu, Tieyong Zeng, Sparse representation prior and total variation based image deblurring under impulse noise,  SIAM Journal on Image Sciences,2013, 6(4): 2258-2284 (5)

(41) Liyan Ma, Lionel Moisan, Jian Yu, Tieyong Zeng. A Dictionary learning approach for Poisson image deblurring, IEEE Trans. Medical Imaging, 32(7), pp. 1277-1289 ,2013 (14)

(42) Bian-fang Chai, Jian Yu, et al, Combining a popularity-productivity stochastic block model and a discriminative content model for general structure detection, Physical Review E. 2013, 88(1): 012807

(43) Liyan Ma, Michael K. Ng, Jian Yu, Tieyong Zeng. Efficient box-constrained TV-type-l1 Algorithms for Restoring Images with Impulse Noise. Journal of Computational Mathematics, 31(3):249-270, 2013 (4)

(44) Jian Yu, M.S. Yang, Pengwei Hao, Clustering construction on a multimodal probability model, Information Sciences, 237:211-220, March, 2013

(45) Zhu Yan, Liping Jing, Jian Yu, A novel semi-supervised learning framework with simultaneous text representing, Knowledge and Information Systems, 34(3):547-562, March, 2013

(46) Jiang Y, Jia C, Yu J. An efficient community detection method based on rank centrality. Physica A: Statistical Mechanics and its Applications, 392 (2013) 2182–2194  (7)

(47) 肖宇,于剑,加权的自适应相似度度量,计算机研究与发展, 50(9):1876-1882, 2013.9

(48) 杨柳,于剑,景丽萍, 一种自适应的大间隔近邻分类方法,计算机研究与发展, 50(11):2269-2277, 2013.11

(49) 柴变芳;于剑,贾彩燕,王静红,一种基于随机块模型的快速广义社区发现算法,软件学报,2013,24(11):2699-2709 2013

(50) Yu Xiao, Jian Yu, Partitive clustering (K-means family), WIREs Data Mining and Knowledge Discovery, 2012,2(3):209-225. (6)

(51) Congyan Lang, Guangcan Liu, Jian Yu, Shuicheng Yan, Saliency Detection by Multitask Sparsity Pursuit,  IEEE Trans. On Image Processing, 2012,21(3):1327-1338  (51)

(52) J. Yun, Liping Jing, J. Yu and H. Huang, A multi-layer text classification framework based on two-level representation model, Expert systems with applications, 2012, 39 (2):2035-2046

(53) Wen-Liang Hung, Miin-Shen Yang, Jian Yu, Chao-Ming Hwang, Feature-Weighted Mountain Method with Its Application to Color Image Segmentation,International Journal of Computational Intelligence Systems, 4-5,1002 - 1011, 2011

(54) Jian Yu, Minn-Shen Yang, Pengwei Hao, A Novel Multimodal Probability Model for Cluster Analysis, Fundamenta Informaticae,111(1):81-90,2011

(55) Jian Yu, Miin-Shen Yang, E. Stanley Lee: Sample-weighted clustering methods. Computers & Mathematics with Applications 62(5): 2200-2208 (2011)  )(3)

(56) Yu Xiao, Tieyong Zeng, Jian Yu, Michael K. Ng: Restoration of images corrupted by mixed Gaussian-impulse noise via l1-l0 minimization. Pattern Recognition 44(8): 1708-1720 (2011)  (48)

(57) 于剑,相似性的二值表示,《计算机研究与发展》, 47(12):2117-2122, 2010, 12

(58) Liping Jing, Jiali Yun, Jian Yu, Houkuan Huang: Text Clustering via Term Semantic Units. Web Intelligence 2010: 417-420

(59) Jian Yu, Shuigeng Zhou, Lipo Wang, Jingsheng Lei, “Preface: Advances in Fuzzy Sets and Knowledge Discovery”, Computers and Mathematics with applications, 57(6): 865, Mar. 2009.

(60) 肖  宇,    , “基于近邻传播算法的半监督聚类”, 软件学报,19(11): 2803-2813, 2008年11月 (30)

(61) Miin-Shen Yang, Kuo-Lung Wu, June-Nan Hsieh and Jian Yu,“Alpha-Cut Implemented Fuzzy Clustering Algorithms and Switching Regressions”,IEEE Transactions on Systems, Man and Cybernetics-part B: Cybernetics,38(3): 588-603, 2008  (28)

(62) Jian Yu, Minn-Shen Yang, “A Generalized Fuzzy Clustering Regularization Model with Optimality Tests and Model Complexity Analysis”, IEEE Transactions On Fuzzy Systems,15(5): 904-905, Oct. 2007  (26)

(63) Jian Yu, “From the Guest Editor: Special Issue on fuzzy clustering and its applications”, International Journal of Fuzzy Systems, 9(4):187, December, 2007

(64) 于剑,“聚类算法的新进展:谱聚类综述”, 机器学习及其应用2007, 清华大学出版社, 2007,10

(65) Jian Yu, Pengwei Hao, “A novel insight into learning theory: The gap between teaching and learning”, International Journal of Fuzzy Systems, 9(4): 212-219,December, 2007

(66) Jian Yu, Cuixia Li, “A Novel cluster validity index for FCM algorithm”, Journal of Computer Science and Technology, 21(1), 137-140, Jan. 2006  (9)

(67) 邵超 黄厚宽 于剑, 基于进化规划的Markov随机场参数的估计, 模式识别与人工智能, 2006年 19卷 2期, 143-148

(68) Jian Yu, “General c-means clustering model ”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), 1197-1211, Aug. 2005  (57)

(69) Jian Yu, Minn-Shen Yang, “A Note on the ICS Algorithm with Corrections and Theoretical Analysis”, IEEE Trans. On Image Processing, 14(7), 973-978, July 2005

(70) Jian Yu, Pengwei Hao, “Comments on ‘The Multisynapse Neural Network and its Application to Fuzzy Clustering’”, IEEE Transactions on Neural Networks, 16(3), 777-778, May, 2005

(71) Jian Yu, Chao Shao, Youfang Lin, Houkuan Huang, “why m>1 in the FCM algorithm”, Chinese Journal of Electronics, 14(2): 215-219, April, 2005

(72) K-L. Wu, J. Yu and M-S. Yang “A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality tests”, Pattern Recognition Letters, 26(5):639-652,April, 2005 (32)

(73) Jian Yu, Minn-Shen Yang, “Optimality Test for a Generalized FCM and Its Application to Parameter Selection”, IEEE Trans. On Fuzzy Systems, 13(1),164-176, Feb.2005  (56)

(74) 李翠霞, 于剑,一种模糊聚类算法归类的研究, 北京交通大学学报,2005年 第29卷 第02期: 17-21   (16)

(75) 张敏, 于剑,“基于划分的模糊聚类算法”, 软件学报, 2004,15(6),858-868 (127)

(76) Jian Yu, Q. Cheng, Houkuan Huang, “Analysis of the weighting exponent in the FCM”, IEEE Transactions on Systems, Man and Cybernetics-part B: Cybernetics, 34(1), 634-639, Feb.2004 (103)

(77) Jian Yu, Hongbo Shi, Houkuan Huang, et al. “Counterexamples to convergence theorem of the maximum entropy clustering algorithm”, Science in China, series F, vol.46, no.5, 321-326,Oct.2003

(78) 于剑, “论模糊c均值算法的模糊指数”, 计算机学报, vol.26 (8), 968-973,2003.8 (52)

(79) 于剑,石洪波,黄厚宽等, “关于极大熵聚类算法的收敛性定理的反例”, 中国科学,E辑,33(6), 531-536, 2003.6

(80) 于剑, “FCM算法中的权重指数m的一点注记”, 电子学报, 31(3), 478-480, 2003.3 (24)

(81) Jian Yu, Houkuan Huang, “A weighting fuzzy c-means algorithm”, FUZZ-IEEE 2003, v.2, 896-901, May, 2003

(82) Jian Yu, Houkuan Huang, “An efficient optimality test for the fuzzy c-means algorithm”, FUZZ-IEEE 2002, v.1, 98-103, May, 2002 (19)

(83) 于剑, 程乾生,“模糊聚类方法中的最佳聚类数的存在范围”,中国科学,E辑,32(2),274-280, 2002.2  (78)

(84) Jian Yu, Qiansheng Cheng, “The upper bound of the optimal number of clusters in fuzzy clustering”, Science in China, series F, vol.44, no.2, pp.119-125, April 2001(19)

(85) 于剑, 程乾生, “关于聚类有效性函数FP(u,c)”, 电子学报, vol.29, no.7, pp.899-901, 2001.7

(86) Jian Yu, Qiansheng Cheng, “A note on rough set and non-measurable set”, Chinese Science Bulletin, 45(16), 1456-1458, Aug. 2000

(87) 于剑, 程乾生, “粗集与不可测集”, 科学通报,45(7),686-688, 2000.4

专著/译著

于剑著,《机器学习:从公理到算法》,清华大学出版社,2017年7月出版

李德毅(主编)、于剑(执行主编):《人工智能导论》,中国科学技术出版社,2018年8月


专利

软件著作权

获奖与荣誉

2006年获得霍英东青年教师基金

2006年入选教育部新世纪优秀青年人才支持计划





社会兼职


2020.9-

中国人工智能学会会士(CAAI Fellow

2020.012023.12

中国计算机学会人工智能与模式识别专委会主任

2019.10-

中国人工智能学会副秘书长兼常务理事

2019.102022

教育部高等学校计算机类专业教学指导委员会人工智能专家委员会委员

2018.12

智能计算与信息处理教育部重点实验室学术委员

2018.08

Chinese Journal of Electronics 编委

2018.03

高等教育出版社“新一代人工智能教材编委会”编委

2018.01

中国计算机学会会士(CCF Fellow

2017.08

《模式识别与人工智能》编委

2017.01

智能交通数据安全与隐私保护技术北京市重点实验室学术委员

2016.12

山西大学计算智能与中文信息处理教育部重点实验室学术委员

2016.012019.12

中国计算机学会人工智能与模式识别专委会秘书长

2015.8

《计算机研究与发展》编委

2012.8

《计算机学报》编委

2012.4-

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2012.2

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2012.2

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2011.3

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2010.12

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2010.8

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2008.4

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2008.42015.12

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