邵俊明
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Give a talk for the 2nd Big Data Seminar at UESTC, Chengdu, Nov. 2013. Slides
Give a talk for the 1st Big Data Seminar at UESTC, Chengdu, 2013. Slides
Invited talk at Northwest A&F University, Yangling, 2013.
Attend the IEEE International Conference on Data Mining (ICDM) in Brussel and give a talk, 2012.
Attend the conference Organization for Human Brain Mapping (OHBM) and present a poster, Beijing, 2012.
Talk at IEEE International Conference on Data Mining (ICDM), Vancouver, 2011.
Presentation at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Barcelona, 2010.
Talk at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Washington, 2010.
Give a talk at European Workshop on Mining Massive Data Sets (EMMDS), Denmark, 2009.
Give a talk at International Conferences on Computational Intelligence for Modeling, Control and Automation (CIMACA), Vienna, 2008.
Acitivities
Revewing on data mining related journals, such as IEEE Transaction on Knowledge and Data Engineering (TKDE), Artifical Intelligence , Chaos, World Scientific, Database Technology for Life Sciences and Medicine, International Journal of Computer Mathematics, etc. Also as the PC memeber for major data mining conferences, such as ECML/PKDD.
2001.9 -- 2005.7
西北农林科技大学
 计算机科学与技术
 大学本科毕业
 工学学士学位
2005.9 -- 2008.7
西北农林科技大学
 计算机应用技术
 硕士研究生毕业
 工学硕士学位
2008.9 -- 2011.11
慕尼黑大学
 计算机科学
 博士研究生毕业
 理学博士学位
2011.11 -- 2012.7
Technical University of Munich (Germany)
2008.9 -- 2011.11
University of Munich (Germany)
 博士研究生
 博士学位
2013.12 -- 至今
电子科技大学计算机科学与工程学院 教授
2012.8 -- 2013.12
德国美因茨大学计算机学院 洪堡学者
2011.11 -- 2012.7
德国慕尼黑工业大学 博士后
2011.8 -- 2012.12
University of Mainz (Germany), Alexander von Humboldt Fellow
Multi-source heterogeneous data mining
Brain network mining and applications (Mining on fMRI/DTI/EEG brain data)
Data stream mining (Concept drift detection/clustering/classification)
Clustering (scalable/subspace/hierarchical/parameter-free clustering)
Subspace Clustering, Community Detection, Data Stream Clustering and Classification, Brain Network Mining, Machine Learning