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James Z. Wang (born 1972) is an associate professor of the College of Information Sciences and Technology, the Department of Computer Science and Engineering, and the Integrative Biosciences (IBIOS) Program (Option on Bioinformatics and Genomics)[1] at the Pennsylvania State University, USA. He is also the Vice Director of the Intelligent Information Systems Laboratory[2] and a policy committee member of the I3C infrastructure. He was a Visiting Professor of the Robotics Institute, Carnegie Mellon University during 2007–2008.



Wang received a summa cum laude Bachelor's degree in Mathematics and Computer Science from University of Minnesota, an M.S. in Mathematics and an M.S. in Computer Science, both from Stanford University, and a Ph.D. degree in Medical Information Sciences from Stanford University's Biomedical Informatics and Database groups (advisor: Gio Wiederhold).


Wang is the author or coauthor of two monographs and nearly 100 journal articles, book chapters, and refereed conference papers, including one coauthored paper published in Science. His works have been widely cited. For example, SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries has been received more than 500 citations.

He has carried out work with the Biomedical Informatics Group and the Computer Science Database Group at Stanford that makes possible the retrieval of specific images from databanks of images. He has co-developed the SIMPLIcity semantics-sensitive image retrieval system and the ALIPR automatic linguistic indexing of pictures system. These systems have been applied to several domains including biomedical image analysis, satellite imaging, and art and cultural imaging. The SIMPLIcity system has been sought after and obtained by researchers from more than 60 institutions.

His studies have also involved retrieval from large-scale genome databases through pattern recognition. His research work has been reported widely by significant media including Discovery, Scientific American, MIT Tech Review, Public Radio, NPR, and CBS.

Wang has served as a Program Committee Vice Chair for the 12th International World Wide Web Conference and as an ad hoc reviewer for 40+ scientific journals and many conferences. He has served on the EU/DELOS-US/NSF Working Group on Digital Imagery for Significant Cultural and Historical Materials and provided a written testimony at the National Academies Committee on Tools and Strategies for Protecting Kids from Pornography and Their Applicability to Other Inappropriate Internet Content.

Wang was featured in a PBS series NOVA science. He contributed in developing new computerized methods to help detect fake Van Gogh paintings by analyzing the direction and amount of brushstrokes in the painting, as compared to original Van Gogh's. He was successful in determining the fake version of the painting, produced by Charlotte Caspers, from the original.


Wang has been a recipient of an NSF Career award and the endowed PNC Technologies Career Development Professorship (provided to Penn State by the PNC Foundation).



Representative peer-reviewed papers

  • James Z. Wang, Jia Li and Gio Wiederhold, "SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 9, pp. 947–963, 2001. [An abstract in D-LIB, 1999]
  • Datta, Ritendra; Dhiraj Joshi, Jia Li, James Z. Wang (2008). "Image Retrieval: Ideas, Influences, and Trends of the New Age". ACM Computing Surveys.  
  • Jia Li and James Z. Wang, ``Real-time Computerized Annotation of Pictures, IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted in December 2007. [An abstract was published in Proc. ACM Multimedia, 2006.]
  • Jia Li and James Z. Wang, "Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1075–1088, 2003.
  • James Z. Wang, Gio Wiederhold, Oscar Firschein and Sha Xin Wei, "Content-Based Image Indexing and Searching Using Daubechies' Wavelets, International Journal on Digital Libraries, vol. 1, no. 4, pp. 311–328, 1998. [An abstract in ADL 1997 and was selected as one of the best papers]
  • Yixin Chen and James Z. Wang, "A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 1252–1267, 2002. [An abstract was published in Proc. ACM Multimedia, 2001]
  • Yixin Chen and James Z. Wang, "Image Categorization by Learning and Reasoning with Regions, Journal of Machine Learning Research, vol. 5, 913-939, August 2004.
  • Yixin Chen, James Z. Wang and Robert Krovetz "CLUE: Cluster-based Retrieval of Images by Unsupervised Learning, IEEE Transactions on Image Processing, vol. 14, no. 8, pp. 1187–1201, 2005.
  • James Z. Wang, Jia Li, Gio Wiederhold and Oscar Firschein, "System for Screening Objectionable Images, Computer Communications, vol. 21, no. 15, pp. 1355–1360, Elsevier, 1998. [An abstract was presented in IDMS 1997 and was selected as one of the best papers]
  • Yixin Chen, Jinbo Bi and James Z. Wang, "MILES: Multiple-Instance Learning via Embedded Instance Selection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 12, pp. 1931–1947, 2006.
  • Dhiraj Joshi, James Z. Wang and Jia Li "The Story Picturing Engine - A System for Automatic Text Illustration, ACM Transactions on Multimedia Computing, Communications and Applications, vol. 2, no. 1, pp. 68–89, 2006.
  • Ritendra Datta, Weina Ge, Jia Li and James Z. Wang, "Toward Bridging the Annotation-Retrieval Gap in Image Search, IEEE MultiMedia, vol. 14, no. 3, pp. 24–35, 2007.
  • Dhiraj Joshi, Jia Li and James Z. Wang, ``A Computationally Efficient Approach to the Estimation of Two- and Three-dimensional Hidden Markov Models, IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1871–1886, 2006.
  • Dean R. Snow, Mark Gahegan, C. Lee. Giles, Kenneth G. Hirth, George R. Milner, Prasenjit Mitra and James Z. Wang, "Cybertools and Archaeology, Science, vol. 311, issue. 5763, pp. 958–959, February 17, 2006.
  • Jia Li and James Z. Wang, "Studying Digital Imagery of Ancient Paintings by Mixtures of Stochastic Models, IEEE Transactions on Image Processing, vol. 13, no. 3, pp. 340–353, 2004.


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