Dr. Wang has been a faculty member of the college since 2000. He is the author or co-author of two monographs and over 65 journal articles. The mission of his research group is to advance knowledge related to the analysis, management, and making sense of large and complex visual data, and to contribute to society through the dissemination of research findings and education of future leaders in this field. The current research interests of his group include biomedical imaging informatics, robotics, computational psychology, visual art, and fundamental explainable learning methods.
Wang has received an NSF Career award, the Amazon Research Awards (three times), and the endowed PNC Technologies Career Development Professorship. He has served as the lead guest editor of IEEE Transactions on Pattern Analysis and Machine Intelligence Special Issue on Real-world Image Annotation and Retrieval (2008), the general chair of ACM Multimedia Information Retrieval events (2006, 2007, and 2010), and as an invited speaker at more than 110 institutions around the world.
Wang served as Visiting Professor at the Robotics Institute of the School of Computer Science, Carnegie Mellon University (2007-2008), as Program Manager in the Office of the National Science Foundation Director (2011 and 2012), and as Chair of the Faculty Council of the College of Information Sciences and Technology at Penn State (2012-2016). Major news wires and leading science media, including PBS NOVA Science NOW TV Program, Associated Press, FOX Business, AFP, Canadian Press, DPA, Forbes magazine, The Economist magazine, Discovery News, National Public Radio, Technology Review, Scientific American, and Apollo-The International Art Magazine have reported his research. According to Google Scholar, his publications have been cited over 25,500 times and his h-index is 61.
Wang's research seeks to advance knowledge through modeling objects, concepts, aesthetics, and emotions in big visual data. Formerly with the Biomedical Informatics Group and the Computer Science InfoLab at Stanford, he undertakes work that makes possible the understanding of images based on machine learning and statistical modeling. Among other contributions, he and his collaborators have developed the SIMPLIcity semantics-sensitive image retrieval system, the ALIPR real-time computerized image tagging system, and the ACQUINE aesthetic quality inference engine. Their research has been applied to several domains including biomedical image analysis, satellite imaging, photography, and art and cultural imaging.
Wang's research has been primarily funded by the National Science Foundation. At Penn State, Wang teaches theoretical foundations of information science, discrete mathematics, techniques related to the organization of data, and medical informatics. He also guides a group of both graduate and undergraduate researchers.
Past Ph.D. students of Wang's 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, DeepMap.AI, Facebook, Google Research, HP Labs, IBM Research, IDIAP Switzerland, Kodak Research, MathWorks, Merck Research, NEC Research, PNC, Siemens Research, SONY Research, Telefonica R&D Barcelona, Toutiao, Twitter, Verisk Analytics, Xerox PARC, Yahoo!, and 12Sigma, among others. Undergraduate research students have pursued graduate study at Brown University, Carnegie Mellon University, Cornell University, Johns Hopkins University, Tufts University, University of Cambridge, and the University of Pennsylvania, among others. His group welcomes talented and motivated graduate and undergraduate students with strong computational and mathematical/statistical skills.