Jun Zhang

Ph.D.

Artificial Intelligence Research Laboratory

Department of Computer Science

Iowa State University, Ames, IA 50011

Contact Info.

• Mailing Address:   226 Atanasoff Hall, Ames, Iowa 50011-1040
• Email Address:
• Office: 214 Antansoff Hall
• Office Phone: (515) 294-7331

Research Interests.

• Machine Learning, Knowledge Discovery and Data Mining
• Ontology Driven Learning, Distributed Learning
• Learning from Semantically Heterogeneous and Partially Specified Data
• Statistical Learning and Graphical Models
• Computational Biology and Bioinformatics
• Evolutionary Computation, Neural Networks, and Nature Inspired Computation

 Education.

• Ph.D. candidate: Computer Science, IOWA STATE UNIVERSITY. Advisor: Prof. Vasant Honavar.
• M.S.: Computer Engineering. UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA.
• B.S.: Computer Science. HEFEI UNIVERSITY OF TECHNOLOGY, CHINA.

 Professional Activities.

• Student Member of AAAI, IEEE, and member of IMLS, and CILD.

  Publications.

Ph.D. Dissertation.

Learning Ontology Aware Classifiers. Jun Zhang (2005) Iowa State University.  

( Research Excellence Award )

Software and Data.

AVT-guided Decision Tree Learning Algorithm
AVT-based Naive Bayes Learning Algorithm

Recent Publications.

Jun Zhang, D. Caragea, and V. Honavar. (2005). Learning Ontology-aware Classifiers. In: Proceedings of the 8th International Conference on Discovery Science. Lecture Notes in Computer Science, Vol. 3735, Springer-Verlag.

D. Caragea, Jun Zhang, J. Bao, J. Pathak, and V. Honavar. (2005). Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous Information Sources (Invited paper). In: Proceedings of the 16th International Conference on Algorithmic Learning Theory. Lecture Notes in Computer Science, Vol. 3734, Springer-Verlag.

Jun Zhang, D.-K. Kang, A. Silvescu, and V. Honavar. (2005). Learning Accurate and Concise Naive Bayes Classifiers from Attribute Value Taxonomies and Data.  Journal  of Knowledge and Information Systems.

 

D.-K. Kang, Jun Zhang, A. Silvescu, and V. Honavar. (2005). Multinomial Event Model Based Abstraction for Sequence and Text Classification. In: Proceedings of Symposium on Abstraction Reformulation, and Approximation (SARA-2005). LNCS, Springer-Verlag.

 

F. Wu, Jun Zhang, and V. Honavar. (2005). Learning Classifiers Using Hierarchically Structured Class Taxonomies. In: Proceedings of Symposium on Abstraction Reformulation, and Approximation (SARA-2005). LNCS, Springer-Verlag.

 

Jun Zhang, and V. Honavar. (2004). AVT-NBL: An Algorithm for Learning Compact and Accurate Naive Bayes Classifiers from Attribute Value Taxonomies and Data. In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM '04). Brighton, UK.

 

Jun Zhang, and V. Honavar. (2004). Learning Naïve Bayes Classifiers from Attribute Value Taxonomies and Partially Specified Data. In: Proceedings of the International Conference on Intelligent System Design and Applications (ISDA 2004).

 

J. Joo, Jun Zhang, J. Yang, V. Honavar. (2004). Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data. In: Proceedings of the 7th International Conference on Discovery Science (DS'04).

 

D.-K. Kang, A. Silvescu, Jun Zhang, V. Honavar. (2004). Generation of Attribute Value Taxonomies from Data for Data-Driven Construction of Accurate and Compact Classifiers. In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM '04).

 

Jun Zhang, and V. Honavar. (2003). Learning Decision Tree Classifiers from Attribute Value Taxonomies and Partially Specified Data. In: Proceedings of the Twentieth International Conference on Machine Learning (ICML-03). Washington, DC.

 

Jun Zhang, A. Silvescu, V. Honavar. (2002). Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction. In: Proceedings of Symposium on Abstraction, Reformulation, and Approximation (SARA-2002). LNCS Vol. 2371. Springer-Verlag.

(See a longer list of Publications.)                        (Download papers from CILD Publications.)

  

Copyright(c) 2005 Jun Zhang. All rights reserved.