个人简历

LAMDA, School of Artificial Intelligence, Nanjing University, China
Brief Biography
Currently I am a Professor at LAMDA led by Professor Zhi-Hua Zhou, my Ph. D. supervisor.
I received my B. Sc. and Ph. D. degrees in computer science from Department of Computer Science and Technology, Nanjing University, China, in 2003 and 2008, respectively. I joined Department of Computer Science and Technology of Nanjing University in 2008.My major research interests include machine learning and data mining, especially on software mining. major research interests include machine learning and data mining, especially on software mining. I have served as the area chair of IEEE ICDM, senior PC member of the premium conferences in artificial intelligence such as IJCAI and AAAI, and PC members for other premium conferences such as KDD, NIPS, ICML, etc., and the chair of the International Workshop on Software Mining. I have served as the associate editor (junior) for Frontiers of Computer Science and editorial board member for International Journal of Data Warehousing and Mining. I am the executive board member of ACM SIGKDD China Chapter. I have been granted various awards including the PAKDD Early Career Award, the Excellent Youth Award from NSFC, the New Century Excellent Talents program of the Education Ministry of China, the CCF Distinguished Doctoral Dissertation Award, and Microsoft Fellowship Award, etc.
Professional Activities
Associate Editor /Editorial Board Member\t
Frontiers of Computer Science (Springer)
International Journal of Data Warehousing and Mining (IGI)
International Journal of Data Mining, Modeling and Management (InderScience)
Acta Automatica Sinica (Science Press)
Journal of Frontiers of Computer Science and Technology (Science Press)
Program Committee Co-Chairs\t
SoftwareMining'18 (The 7th Interenational Workshop on Software Mining, in conjunction with ASE'18)
SoftwareMining'17 (The 6th Interenational Workshop on Software Mining, in conjunction with ASE'17)
SoftwareMining'16 (The 5th Interenational Workshop on Software Mining, in conjunction with ASE'16)
SoftwareMining'15 (The 4th Interenational Workshop on Software Mining, in conjunction with ASE'15)
SoftwareMining'14 (The 3rd Interenational Workshop on Software Mining, in conjunction with ICDM'14)
SoftwareMining'13 (The 2nd Interenational Workshop on Software Mining, in conjunction with ASE'13)
SoftwareMining'12 (The 1st Interenational Workshop on Software Mining, in conjunction with KDD'12)
DSDM'11 (The 1st PAKDD Doctoral Symposium on Data Mining)

Area Chair / Senior\t PC Member
IJCAI'21 (The 30th International Joint Conference on Artificial Intelligence)
IJCAI'20 (The 29th International Joint Conference on Artificial Intelligence)
AAAI'20 (The 34th AAAI Conference on Artificial Intelligence)
ECAI'20 (The 28th International Joint Conference on Artificial Intelligence)
PAKDD'20 (The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining)
IJCAI'19 (The 28th International Joint Conference on Artificial Intelligence)
AAAI'19 (The 33rd AAAI Conference on Artificial Intelligence)
PAKDD'19 (The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining)
ICDM'18 ( The 2018 IEEE International Conference on Data Mining)
IJCAI'18 (The 27th International Joint Conference on Artificial Intelligence)
AAAI'18 (The 32nd AAAI Conference on Artificial Intelligence)
IJCAI'17 (The 26th International Joint Conference on Artificial Intelligence)
AAAI'17 (The 31st AAAI Conference on Artificial Intelligence)
IJCAI'16 (The 25th International Joint Conference on Artificial Intelligence)
PAKDD'16 (The 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining)
PAKDD'15 (The 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining)
\t \t
PC Member\t
KDD'21 (The 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining)
NeurIPS'21 (The 35th Conference on Neural Information Processing Systems)
ASE'21 (The 36th IEEE/ACM International Conference on Automated Software Engineering)
ICDM'21 (The 2021 IEEE International Conference on Data Mining)
ICSME'21 (2021 IEEE International Conference on Software Maintenance and Evolution)
\t
Local Arrangement\tCo-Chair
ACML'09 (The 1st Asian Conference on Machine Learning)
MLA'10 (The 8th Chinese Workshop on Machine Learning and Applications)
MLA'09 (The 7th Chinese Workshop on Machine Learning and Applications)
MLA'08 (The 6th Chinese Workshop on Machine Learning and Applications)\t
Publicity Co-Chair\tPAKDD'12 (The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining)
Teaching
Data Mining for Complex Data Objects Spring 2020, 2019, 2018, 2017, 2016, 2015
Introduction to Data Mining Spring 2020, 2019, 2018, 2017, 2016, 2015
Advanced Data Mining Spring 2019
Artificial Intelligence Spring 2014, 2013, 2012, 2011
Data Mining (081202B3) Fall 2011, 2010, 2009
Digital Image Processing Spring 2009

研究领域

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

近期论文

X. Huo, F. Thung, M. Li, D. Lo, and S.-T. Shi.Deep transfer bug localization. IEEE Transactions on Software Engineering, 2021, 47(7):1368-1380.
Y. Fan, M. Li.Towards generating summaries for lexically confusing code through code erosion. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), Montreal, Canada, 2021, pp. 3721-3727.
X. Huo, M. Li, and Z.-H. Zhou. Control flow graph embedding based on multi-instance decomposition for bug localization. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20), New York, NY, 2020.
S.-T. Shi, W. Zheng, J. Tang, Q.-G. Chen, Y. Hu, J. Zhu, and M. Li. Deep time-stream framework for click-through rate prediction by tracking interest evolution. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20), New York, NY, 2020.
Y.-Y. Zhang and M. Li. Find me if you can: Deep software clone detection by exploiting the contest between the plagiarist and the detector. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019.
S.-T. Shi, M. Li,, D. Lo, F. Thung, and X. Huo. Automatic code review by learning the revision of source code. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019.
Z.-Y. Shen and M. Li. T2S: Domain adaptation via model-independent inverse mapping and model reuse. In: Proceedings of the 18th International Conference on Data Mining (ICDM'18), Singapore, 2018, pp.1224-1229.
Z. Xie and M. Li. Cutting the software building efforts in continuous integration by semi-supervised online AUC optimization. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, pp.2875-2881.
H.-H. Wei and M. Li. Positive and unlabeled learning for detecting software functional clones with adversarial training. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, pp.2840-2846.
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, pp.4310-4317.
A.-S. Ni and M. Li. ACONA: active online model adaptation for predicting continuous integration build failures. In: Proceedings of the 40th International Conference on Software Engineering: Companion Volume (ICSE'18), Gothenburg, Sweden, 2018, pp.366-367.
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.