Lei Tang

Ph.D Student

I received my B.S. from Department of Computer Science, Fudan University in 2004.  Then, I entered Department of Computer Science & Engineering, Arizona State University as a graduate student. My advisor is Dr. Huan Liu.

Research Interests:

My research interests are in the area of Artificial Intelligence and, more specifically, Machine Learning, Learning from Skewed data, Feature Selection, Text Mining and Web Mining.

  • Data Mining & Machine Learning Group Meeting
  • DMML wiki
  • Advaced Topics in Machine Learning
  • AI meeting

    • Publications:

  • Lei Tang, Huan Liu, Jianping Zhang and Zohreh Nazeri, "Community Evolution in Dynamic Multi-mode Networks", KDD 2008
  • Shuiwang Ji, Lei Tang, Shipeng Yu and Jieping Ye, "Extracting Shared Subspace for Multi-label Classification", KDD, 2008
  • Nitin Agarwal, Huan Liu, Lei Tang and Philip Yu, "Identifying the Influential Bloggers in a Community", First ACM International Conference on Web Search and Data Mining, WSDM, 2008
  • Lei Tang, Huan Liu, Jianping Zhang, Nitin Agarwal and John Salerno, " Topic Taxonomy Adaptation for Group Profiling", ACM Transactions on Knowledge Discovery from Data, TKDD, vol 1, issue 4, 2008
  • Payam Refaeilzadeh, Lei Tang and Huan Liu, "On Comparison of Feature Selection Algorithms", The AAAI-07 Workshop on Evaluation Methods for Machine Learning II, 2007
  • Lei Tang, Jianping Zhang and Huan Liu, " Acclimatizing Taxonomic Semantics for Hierarchical Content Categorization", KDD'06 (Slides)
  • Lei Tang, Jianping Zhang and Huan Liu, " Automatically Adjusting Content Taxonomies for Hierarchical Classification", SDM 2006 Workshop on Text Mining
  • Lei Tang and Huan Liu, " Bias Analysis in Text Classification for Highly Skewed Data", ICDM 2005. (Slides)
    •     The full version of the paper is available in the technical report: TR-05-008, Dept. of CSE, ASU

    Contact Information:

    Department of Computer Science  & Engineering,  Arizona State University,

             Tempe, AZ 85287-8809, U.S.

    (480) 727-7808     (480) 965-2751