Dr. James Z. Wang

The article Researchers teach computers how to name images by “thinking” said

Penn State researchers have “taught” computers how to interpret images using a vocabulary of up to 330 English words, so that a computer can describe a photograph of two polo players, for instance, as “sport”, people”, “horse”, and “polo”.
 
The new system, which can automatically annotate entire online collections of photographs as they are uploaded, means significant time-savings for the millions of Internet users who now manually tag or identify their images. It also facilitates retrieval of images through the use of search terms, said James Wang, associate professor in the Penn State College of Information Sciences and Technology, and one of the technology’s two inventors.

Dr. James Z. Wang is a tenured Associate Professor of the College of Information Sciences and Technology and a graduate faculty in the Department of Computer Science and Engineering and the Integrative Biosciences (IBIOS) Program (Option on Bioinformatics and Genomics) at The Pennsylvania State University. He is also the Vice Director of the Intelligent Information Systems Laboratory, a member of the Advisory Board of the Institute for Computational Science, an elected member of the Penn State Graduate Council (2006–2007), and a policy committee member of the I3C infrastructure.
 
James 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 (adviser: Gio Wiederhold). He has been a recipient of an NSF Career award and the endowed PNC Technologies Career Development Professorship.
 
Research interests of his group include semantics-sensitive image retrieval, image security, learning-based linguistic indexing of images/image annotation, biomedical informatics, computational aesthetics, story picturing, art image retrieval, wavelet based retrieval, and computer vision. The group has published two monographs and about 20 journal articles. His group has been invited as referee for about 60 scientific journals. The SIMPLIcity system Wang co-developed with Jia Li in 1999 has been sought after and obtained by researchers from close to 100 institutions. Their work has been widely cited.
 
He authored Integrated Region-Based Image Retrieval, and coauthored Machine Learning and Statistical Modeling Approaches to Image Retrieval, SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries, Content-based Image Indexing and Searching Using Daubechies’ Wavelets, Studying Aesthetics in Photographic Images Using a Computational Approach, Cybertools and Archaeology, MILES: Multiple-Instance Learning via Embedded Instance Selection, and A Computationally Efficient Approach to the Estimation of Two- and Three-dimensional Hidden Markov Models. Read a full list of his publications!