My current research interests include machine learning, data mining, information retrieval. I've worked on learning from labeled and unlabeled data, multi-instance learning, ensemble learning. I've been in charge of a research project of Graduate Innovation Program of Jiangsu Province on Semi-supervised Learning. Currently, I serve as the formal reviewer of ACM T-IS, ACM T-KDD, ACM T-IST, ACM T-DS, IEEE T-KDE, IEEE T-NN, IEEE T-SMCB, IEEE T-SMCC, etc., and served as PC members of IJCAI, AAAI, KDD, IEEE ICME, CIKM, ACML,etc. I participated in PAKDD'06 Data Mining competition with other LAMDA members, and won the Open Category Champion. For the achievements having been made, I have been granted a number of awards and honors, such as CCF Excellent Doctoral Dissertation Award, Microsoft Fellowship Award, etc.

Research Interest

My current research interests mainly include Machine Learning, Data Mining, especially on Software Mining.

Selected Publications     [Full List]

• 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.

• 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.

• Y. Yu, D.-C. Zhan, X.-Y. Liu, M. Li, and Z.-H. Zhou. Predicting future customers via ensembling gradually expanded trees. International Journal of Data Warehousing and Mining, 2007, 3(2): 12-21. Invited paper for the PAKDD'06 Data Mining Competition (Open Category) Grand Champion Team

• 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.

• Z.-H. Zhou, K. Jiang, and M. Li. Multi-instance based web mining. Applied Intelligence, 2005, 22(2): 135-147.

• M. Li, X.-B. Xue, Z.-H. Zhou. Exploiting multi-modal interactions: A unified framework. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp. 1120-1125. 

• D.-C. Zhan, M. Li, Y.-F. Li, and Z.-H. Zhou. Learning instance specific distances using metric propagation. In: Proceedings of the 26th International Conference on Machine Learning (ICML'09), Montreal, Canada, 2009, pp. 1225-1232.

• A. B. Goldburg, M. Li, and X. Zhu. On manifold regularization: A new learning setting and empirical study. In: Proceedings of the 19th European Conference on Machine Learning (ECML'08), LNAI 5211, Antwerp, Belgium, 2008, pp. 393-407.

• M. Li, Z. Zhang, and Z.-H. Zhou. Mining bulletin board systems using community generation. In: Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'08), Osaka, Japan, LNAI 5012, 2008, pp.209-221.

• Z.-H. Zhou and M. Li. Semi-supervised regression with co-training. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI'05), Edinburgh, Scotland, 2005, pp.908-913.

• M. Li and Z.-H. Zhou. SETRED: self-training with editing. In: Proceedings of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'05), Hanoi, Vietnam, LNAI 3518, 2005, pp.611-621.