Ze Tian
Computational Biology Group
Department of Computer Science and Engineering
University of Minnesota, Twin Cities
Minneapolis, MN 55455, USA
Tel: 1-612-625-8544
Homepage: http://www.cs.umn.edu/~tianze/
Email: email

About Me

Ze Tian was a PhD student at Department of Computer Science and Engineering, University of Minnesota. His research interests involve machine learning and data mining. He is currently working at Microsoft.

Research Interest

Machine Learning: SVM, kernel methods and graph-based learning algorithms
Data Mining: Supervised pattern mining algorithms

Educational Background

Publication

  1. Huanan Zhang, Ze Tian and Rui Kuang, Transfer Learning Across Cancers on DNA Copy Number Variation Analysis. IEEE International Conference on Data Mining (ICDM), 2013. [PDF]
  2. Ze Tian, Huanan Zhang and Rui Kuang, Sparse Group Selection on Fused Lasso Components for Identifying Group-specific DNA Copy Number Variations. IEEE International Conference on Data Mining (ICDM), 2012. [PDF] (Best Student Paper Award)
  3. Ze Tian and Rui Kuang, Global Linear Neighborhoods for Efficient Label Propagation, Proceedings of the Twelfth SIAM International Conference on Data Mining (SDM), 2012. [PDF]
  4. Ze Tian and Rui Kuang, Integrative Classification and Analysis of Multiple ArrayCGH Datasets with Probe Alignment, Bioinformatics, 26(18):2313-2320, 2010. [PDF]
  5. Rohit Gupta, Smita Agrawal, Navneet Rao, Ze Tian, Rui Kuang and Vipin Kumar, Integrative Biomarker Discovery for Breast Cancer Metastasis from Gene Expression and Protein Interaction Data Using Error-tolerant Pattern Mining, Proceedings of 2nd International Conference on Bioinformatics and Computational Biology (BICoB), 2010.
  6. Ze Tian, TaeHyun Hwang and Rui Kuang, A Hypergraph-based Learning Algorithm for Classifying Gene Expression and ArrayCGH Data with Prior Knowledge, Bioinformatics, 25(21):2831-2838, 2009. [PDF]
  7. Ze Tian, TaeHyun Hwang and Rui Kuang, A Hypergraph-based Learning Algorithm for Classifying Arraycgh Data with Spatial Prior, Proceedings of IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2009. [PDF]
  8. TaeHyun Hwang, Ze Tian, Rui Kuang and Jean-Pierre Kocher, Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction, Proceedings of the Eighth IEEE International Conference on Data Mining (ICDM), 2008. [PDF]
  9. TaeHyun Hwang, Hugues Sicotte, Ze Tian, Baolin Wu, Jean-Pierre Kocher, Dennis A. Wigle, Vipin Kumar and Rui Kuang, Robust and Efficient Identification of Biomarkers by Classifying Features on Graphs, Bioinformatics, 24(18):2023-2029, 2008. [PDF]

Teaching

Internship

Microsoft Research

Programming Skills

Proficient in C/C++, VC++, Java, TCP/IP, MATLAB
Familiar with .NET, C#, Perl, Mathematica, R