Zhang, Jintao Ph.D. Candidate Information Technology and Telecommunication Center Center for Bioinformatics University of Kansas Office: 344EA Nichols Hall, West Campus Phone: (785)393-2819 E-mail: jtzhang AT ku dot edu Research Experience StumbleUpon Download

Research Interest

• Machine learning and data mining algorithms such as multi-task learning, boosting, multi-label classification, and multi-view learning, and applications of these algorithms on important bioinformatics topics: protein-chemical interaction prediction, adverse drug reaction prediction, and etc.
• Semi-supervised learning, supervised clustering, and their applications on real-world problems.
• Chemoinformatics: virtual screening, and etc.

Education

• Ph.D. Candidate in Bioinformatics, University of Kansas, GPA: 3.65, 8/2006 - 5/2012 (expected)
• Master in Chemistry, University of California, Riverside, GPA: 3.66, 9/2002 - 3/2005
• Bachelor in Chemical Physics, University of Science and Technology of China, Hefei, Anhui, China, GPA: 85/100, 9/1996 - 6/2001

Awards

• Departmental Fellowship, University of California, Riverside, 2002-2003
• Outstanding Student Scholarship, USTC, Hefei, Anhui, China, 1996, 1998-1999, 1999-2000
• National Mathematical Contest of High School Students in China, second class medal in Hubei, China, 1995

Programming

• C++/C, Java, FORTRAN90, Perl, MATLAB
• MySQL/PHP/HTML
• Map/Reduce, Hadoop
• Software: Cytoscape, Pajek, RasMol, ClustalW, DALI, BLAST, Pipeline Pilot, Open Babel

Relevant Courses

• Computer Science: C++ Programming, Formal Language, Data Structures and Algorithms, Computer Architecture, Rational Database, Graph Algorithms
• Machine Learning/Data Mining: Machine Learning, Information Retrieval, Computer Vision, Numerical Analysis
• Bioinformatics: Introduction to Bioinformatics, Principle of Bioinformatics, Systems Biology

Publications

1. Jintao Zhang and Jun Huan, Inductive Multi-task Learning with Multiple View Data, to appear in Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, August 2012.
2. Jintao Zhang, Gerald H. Lushington, and Jun Huan, Characterizing Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set, Journal of Chemical Information and Modeling, vol. 51(6), pp. 1205-1215 (2011).
3. Jintao Zhang, Gerald H. Lushington, and Jun Huan, The BioAssay Network and Its Potential Applications to Therapeutic Discovery, BMC Bioinformatics special issue (2011).
4. Yi Jia,Jintao Zhang, and Jun Huan, An efficient graph mining method for complicated and noisy data with real-world applications, Journal of Knowledge and Information Systems (KAIS), pp. 1-25, February 2011.
5. Jintao Zhang, Gerald H. Lushington, and Jun Huan, Exploratory Analysis of the BioAssay Network with Implications to Therapeutic Discovery, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'10) (short paper), Hong Kong, China, December 2010.
6. Jintao Zhang and Jun Huan, Novel Biological Network Feature Discovery for in silico Identification of Drug Targets, in Proceedings of the 1st ACM International Health Informatics Symposium (IHI'10), Arlington, VA, November 2010.
7. Jintao Zhang and Jun Huan, Comparison of Chemical Descriptors for Protein-Chemical Interaction Prediction. International Journal of Computational Bioscience, vol. 1(1), pp. 13-21 (2010).
8. Jintao Zhang and Jun Huan, Analysis of Network Topological Features for Identifying Potential Drug Targets, in the 9th International Workshop on Data Mining in Bioinformatics (BioKDD'10), Washington D.C., July 2010.
9. Yi Jia, Jun Huan, Vincent Buhr, Jintao Zhang, and L. N. Carayannopoulos, Towards Comprehensive Structural Motif Mining for Better Fold Annotation in the "Twilight Zone" of Sequence Dissimilarity. BMC Bioinformatics, vol. 10, pp. S46 (2009).

Hobbies

• Outdoors, international and domestic traveling (west Europe, Las Vegas, Florida, Hawaii, San Diego, ...)
• Reading, movie, and internet.
• Gym, and badminton