James Z. Wang's Research Group

Modeling Objects, Concepts, Aesthetics and Emotions in Images


What's New: September '14 -- Dr. Wang will deliver a keynote talk at the VISART: Where Computer Vision Meets Art workshop of the ECCV 2014 Conference.
June '13 -- Dr. Wang delivered a keynote talk at the Visual Analysis Beyond Semantics workshop of the CVPR 2013 Conference.
October '12 -- Our paper on shape and the computability of emotions is published. (read the paper).
April '12 -- IEEE Transactions on Pattern Analysis and Machine Intelligence spotlights our article on van Gogh's paintings. (read the paper).
December '11 -- Professor Wang gave a talk at the Mathematics: Muse, Maker, and Measure of the Arts workshop in Banff. (photos)
June '10 -- Our aesthetics research was featured on TV with over 47 million viewers in the US and over 200 million viewers internationally.

About the Group: Research interests of this group include automatic image tagging / recognition, climate informatics, biomedical informatics, computability of aesthetics and emotions, semantics-sensitive image retrieval, story picturing, art image analysis and retrieval, and image security. The group has published two monographs and more than 30 journal articles (g-scholar profile). Members of the group have served as referee for over 60 scientific journals in various related fields. The SIMPLIcity system Wang co-developed with Jia Li has been sought after and obtained by researchers from over 100 institutions. Recent systems developed by the group include the ALIPR real-time automatic image annotation system and the Acquine aesthetic quality inference engine. Past Ph.D. students of the group have taken tenure-track faculty and research scientist positions, right after graduation. In the summers, graduate students have participated in internships at Adobe Research, Apple, AT&T Labs, Google Research, HP Labs, IBM Research, IDIAP Switzerland, Kodak Research, Merck Research, NEC Research, SONY Research, Telefonica R&D Barcelona, Xerox PARC, and Yahoo!, among others.

Biography of the PI: James Z. Wang has been on Penn State faculty since 2000, where he is Professor and Faculty Council Chair of the interdisciplinary College of Information Sciences and Technology. He is also Affiliated Professor of the Integrative Biosciences (IBIOS) Program (Option on Bioinformatics and Genomics, the Huck Institutes of the Life Sciences). He serves as the founding Co-Director of the Intelligent Information Systems Laboratory (2001-). He has been a recipient of an NSF Career award (2004-2009) and the endowed PNC Foundation Technologies Career Development Professorship (2000-2006). He has served as the lead guest editor of IEEE Trans. on Pattern Analysis and Machine Intelligence Special Section on Real-world Image Annotation and Retrieval (2008), the General Chair of the ACM Multimedia Information Retrieval (MIR) events (2006, 2007, and 2010, now named ICMR), an Associate Editor of IEEE Transactions on Multimedia (2009-2011), and an invited speaker at more than 70 institutions. He was a Visiting Professor of Robotics at Carnegie Mellon University (2007-2008) and a Program Manager in the Office of the National Science Foundation Director (2011 and 2012). He has held visiting positions at IBM Almaden Research Center, SRI International, NEC Research, and Chinese Academy of Sciences. Wang received a summa cum laude Bachelor's degree in Mathematics and Computer Science from University of Minnesota where his thesis advisor was number theorist Dennis A. Hejhal. From Stanford University, he received an M.S. in Mathematics, an M.S. in Computer Science, and a Ph.D. in Medical Information Sciences where his doctoral thesis advisor was computer science pioneer Gio Wiederhold.

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James Z. Wang, Professor and Faculty Council Chair

College of Information Sciences and Technology
313C IST Building, Penn State, University Park, PA 16802
jwang at ist dot psu dot edu, +1-814-865-7889, (fax) +1-814-865-6426
personal site

This material is based upon work supported by the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

In the midst of difficulty lies opportunity. - Albert Einstein