基本简介

黎铭，博士。分别于2003年、2008 年于南京大学计算机科学与技术系获学士、博士学位。博士毕业后留校任教。现为中国人工智能学会、中国人工智能学会机器学习专委会会员。主要从事机器学习、数据挖掘、信息检索等方面的研究工作。近五年来在IEEE Transactions on Knowledge and Data Engineering、IEEE Transactions on Systems, Man and Cybernetics等国内外重要刊物和会议上发表论文17篇。现担任学术期刊International Journal of Data Mining, Modeling and Management (InderScience) 编委，IEEE Transactions on Systems, Man and Cybernetics - Part C: Applications and Reviews (IEEE)、Knowledge and Information Systems (Springer)、Circuits, Systems & Signal Processing (Springer), Engineering Applications of Artificial Intelligence (Elsevier)、 Science in China, Series E (Springer)等刊物的正式审稿人、国际会议ASONAM‘09, QIMIE‘09程序委员会委员以及KDD‘07、ICDM‘07、NAACL-HLT‘07、PAKDD‘07、ICIC‘07等审稿人。攻读博士期间曾获“微软学者”奖、惠普奖学金等，并作为主要成员之一获PAKDD’06 国际数据挖掘大赛公开组冠军。

发表论文

Selected Publications     [Full List]

  Z. Xie and M. Li. Semi-supervised AUC optimization without guessing labels of unlabeled data. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI‘18), New Orleans, LA, 2018.

X. Huo and M. Li. Enhancing the unified features to locate buggy files by exploiting the sequential nature of source code. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI‘17), Melbourne, Australia, 2017, 1909-1915.

H.-H. Wei and M. Li. Supervised deep features for software functional clone detection by exploiting lexical and syntactical information in source code. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI‘17), Melbourne, Australia, 2017, 3034-3040.

A.-S. Ni and M. Li. Cost-effective build outcome prediction using cascaded classifiers. In: Proceedings of the 14th International Conference on Mining Software Repositories (MSR‘17), Buenous Aires, Argentina, 2017.

X. Huo, M. Li, and Z.-H. Zhou. Learning unified features from natural and programming languages for locating buggy source code. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI‘16), New York, NY, 2016, 1606-1612.  

T.-D. Le, D. Lo, and M. Li. Constrained feature selection for localizing faults. In: Proceedings of the 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME‘15), Bremen, Germany, 2015, pp. 501-505.  

  M. Li, H. Zhang, R. Wu, and Z.-H. Zhou. Sample-based software defect prediction with active and semi-supervised learning. Automated Software Engineering, 2012, 19(2): 201-230.

Y. Jiang, M. Li, and Z.-H. Zhou. Software defect detection with ROCUS. Journal of Computer Science and Technology, 2011, 26(2): 328-342.

Z.-H. Zhou and M. Li. Semi-supervised learning by disagreement. Knowledge and Information Systems, 2010, 24(3): 415-439.

M. Li, H. Li, and Z.-H. Zhou. Semi-supervised document retrieval. Information Processing & Management, 2009, 45(3): 341-355.

Y. Jiang, M. Li, and Z.-H. Zhou. Mining extremely small data sets with application to software reuse. Software: Practice and Experience, 2009, 39(4): 423-440.

M. Li and Z.-H. Zhou. Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples. IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans, 2007, 37(6): 1088-1098.

Z.-H. Zhou and M. Li. Semi-supervised regression with co-training style algorithms. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(11): 1479-1493.

Z.-H. Zhou and M. Li. Tri-training: exploiting unlabeled data using three classifiers. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(11): 1529-1541.  

讲授课程

Teaching   Introduction to Data Mining            

Spring 2018, 2017, 2016, 2015 Artificial Intelligence                        

Spring 2014, Spring 2013, Spring 2012, Spring 2011 Data Mining (081202B3)              

Fall 2011, Fall 2010, Fall 2009 Digital Image Processing                

新闻报导

大咖创新说|黎铭：南京在人工智能领域有原创性潜力

南京大学黎铭教授到我校作“人工智能漫谈”讲座