LOUISIANA CANCER RESEARCH CONSORTIUM AT XAVIER
 
 
 
Kun (Karen) Zhang, Ph.D.
seporator

Dr. Karen Zhang
Position Title: Assistant Professor in Computer Science
Website: http://webusers.xula.edu/kzhang/
Office location: 540 NCF Annex
Office phone: 504-520-6700
Email address: kzhang@xula.edu

Biographical Narrative
Kun (Karen) Zhang received her PhD in Computer Science from Tulane University in 2006 and has been working as Assistant Professor at Xavier University of Louisiana since then. Her main research interests and experiences are in various areas of data mining and bioinformatics. She is particularly interested in developing simple, unconventional, but effective methods to solve challenging real-world problems. Her first-authored paper that uses "Randomized Decision Tree" to predict skewed ozone days won “the best application paper award” at the IEEE 6th International Conference on Data Mining (ICDM2006).  An extended version further comparing Probabilities Estimation Trees (PETs) with SVM, Bagging, AdaBoost and a number of other popular learning algorithms on the same domain was published at the prestigious data mining journal Knowledge and Information Systems. Her later application of PETs to the nuclear radioxenon monitoring problem won the championship of the 8th IEEE ICDM2008 Data Mining Contest. Dr. Zhang is the junior faculty recipient of the 2010 Norman C. Francis Excellence in Scholarship Award. Her current bioinformatics research is funded by National Institution of Health, Louisiana Broad of Regents and Tulane Cancer Center.  Dr. Zhang has established fruitful collaborations with investigators having mutual interests and complementary expertise at IBM T.J Watson Research Center, Tulane Cancer Center, University of New Orleans and University of North Texas. She is the member of ACM, Louisiana Cancer Research Consortium and Louisiana Biomedical Research Network.

Research Overview
Data Mining & Machine Learning:

  • Probability estimation trees,
  • Ensemble methods,
  • Feature discovery and selection,
  • Frequent Pattern Classification

Bioinformatics

  • Insertion site prediction of transposable elements
  • MicroRNA target site prediction

Selected Publications:

  • G. Xu, C. Fewell, C. Taylor, N. Deng, D. Hedges, X. Wang, K. Zhang, H. Zhang, Q. Yin, J. Cameron, M. Lacey, Z. Lin, D. Zhu and E. Flemington, "Transcriptome and targetome analysis in miR-155 expressing cells using RNA-seq", Accepted by RNA
  • H. Chen, Z. Zhao, K. Zhang and D. Zhu, "New Aspects on Haplotype Inference from SNP Fragments", book chapter,  “A Practical Guide to Bioinformatics Analysis”, published by iConcept Press Ltd, 2010
  • K. Zhang, W. Fan, P. Deininger, A. Edwards, Z. Xu and D. Zhu, “Breaking the computational barrier: a divide-conquer and aggregate based approach for Alu insertion site characterization”, International Journal of Computational Biology and Drug Design, 2009;2(4):302-322.               
  • K. Zhang and W. Fan, “Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond”, Knowledge and Information System, 14(3), 2008, Springer.
  • W. Fan and K. Zhang, “Bagging”, invited contribution, Encyclopedia of Database Systems. 2008, Springer
  • W. Fan, E. Zhong, J. Peng, O. Verscheure, K. Zhang, J. Ren, R. Yan and Q. Yang, "Generalized and Heuristic-Free Feature Construction", Proceedings of Tenth SIAM International Conference on Data Mining, 2010
  • E. Zhong, W. Fan, J. Peng, K. Zhang, J. Ren, D. Turaga and O. Verscheure, "Cross Domain Distribution Adaptation via Kernel Mapping", Proceedings of 15th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD09), 2009, Paris
  • W. Fan, K. Zhang, H. Cheng, J. Gao, X. Yan, J. Han, P. S. Yu and O. Verscheure, “Direct Mining of Discriminative and Essential Graphical and Itemset Features via Modelbased Search Tree”, Proceedings of 14th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD08), August, 2008, Las Vegas, NV
  • E. Zhong, S. Xie, W. Fan, J. Ren, J. Peng, and Kun Zhang, "Graph-based Iterative Hybrid Feature Selection", 2008 IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy.
  • K. Zhang, W. Fan, X. Yuan, I. Davidson and X. Li, “Forecasting skewed biased stochastic ozone days: analyses and solutions”, Proceedings of 6th IEEE International Conference on Data Mining (ICDM06), P. 753 - 764, 2006, Best Application Paper Award
  • K. Zhang, W. Fan, B. Buckles, X. Yuan and Z. Xu, “Discovering unrevealed properties of probability estimation trees: on algorithm selection and performance explanation”, Proceedings of 6th IEEE International Conference on Data Mining (ICDM06), P. 741-752, 2006

Current Funding:

  • Principal Investigator, NIH RCMI Program, Pilot Project, “A Hybrid Data Mining Framework for Efficient Characterization of Insertion Preferences of Retrotransposons”,
  • Awarded funds: $500,000, 9/2009 – 7/2014
  •  Principal Investigator,  Louisiana Board of Regents Research Competitiveness Subprogram (BOR-RCS), “A Data Mining Framework to Predict Alu Insertion Sites”,
  • Awarded funds: $107,489, 6/2008 – 6/2011
  •  Co-Investigator, NIH R01 CA130752, Administrative Supplements, Subawarded from Tulane Cancer Center, "Analysis of Epstein Barr virus type III latency on cellular miRNA gene expression",
  • Principal Investigator, Dr. Erik Flemington, Tulane Cancer Center
  • Awarded funds: $57,049, 6/2009 – 9/ 2010

 
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