Zhongfei (Mark) Zhang is a Professor of Computer Science
at State University of New York (SUNY) at Binghamton.
He directs the Multimedia
Research Laboratory at Binghamton.
He has a B.S. (cum laude) in Electronics Engineering,
an M.S. in Information Science, both from Zhejiang University,
Hangzhou, China, and a Ph.D. in Computer Science from the
University of Massachusetts at Amherst. When he was in the graduate school, he also
worked as an Intern student at NEC Research Institute, Inc. at
Princeton, NJ, and as a technical consultant
at Applied Artificial Intelligence, Inc. (formerly Amerinex
Artificial Intelligence, Inc.) at Amherst, MA.
He was a research scientist at the Center
of Excellence for Document Analysis and Recognition
and was in the faculty of the Department of
Computer Science and Engineering, both at SUNY
Buffalo, before he joined the faculty of the Department of Computer Science at SUNY
Binghamton in the Fall of 1999. He also holds many visiting positions including Air Force Research Laboratory in US, Microsoft Research Asia in China, Chuo University and Waseda University in Japan, Carnegie Mellon University in US, and University of Lille 1 in France.
He has published over 100 peer-reviewed academic
papers in leading international journals and conferences
and several invited papers and book chapters,
has edited or co-edited two books, has published two monographs,
has served as reviewers or program committee members
for many international journals and conferences, and has served as grant
review panelists for several governmental and private funding agencies including
NSF and NASA.
His research is supported by federal and state governments, noticeably
He is associate editors and guest editors for several international journals.
Data Mining and Knowledge
Discovery, Multimedia Information Indexing and Retrieval, Computer Vision and Image Understanding,
Pattern Recognition, Medical Imaging, and Bioinformatics.
The very first monograph on multimedia data mining is published and is available at Amazon
The first monograph on relational data clustering is published and is available at Amazon
Bo Long, Zhongfei (Mark) Zhang, and Philip S. Yu, Relational Data Clustering: Models, Algorithms, and Applications, Taylor & Francis Group/CRC Press, 2010, ISBN: 9781420072617
Zhongfei (Mark) Zhang and Ruofei Zhang, Multimedia Data Mining -- A Systematic Introduction to Concepts and Theory, Taylor & Francis Group/CRC Press, 2008, ISBN: 9781584889663
Jian Yao, Zhongfei (Mark) Zhang, Sameer Antani, Rodney Long, and George Thoma, Automatic Medical Image Annotation and Retrieval, Neurocomputing, Elsevier Science Press, Volume 71/10-12, 2008, pp 2012-2022
Xiao-Bing Xue, Zhi-Hua Zhou, and Zhongfei (Mark) Zhang, Improving Web Search Using Image Snippets, ACM Transactions on Internet Technology, ACM Press, in press, 2008
Tianbing Xu, Zhongfei Zhang, Philip S. Yu, and Bo Long, Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State, Proc. IEEE International Conference on Data Mining, Pisa, Italy, December, 2008, (9.6% acceptance rate)
Tianbing Xu, Zhongfei Zhang, Philip S. Yu, and Bo Long, Dirichlet Process Based Evolutionary Clustering, Proc. IEEE International Conference on Data Mining, Pisa, Italy, December, 2008, (9.6% acceptance rate)
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, Robust Foreground Segmentation Based on Two Effective Background Models, Proc. ACM International Conference on Multimedia Information and Retrieval, Vancouver, Canada, October, 2008, (20.0% acceptance rate)
Bo Long, Zhongfei (Mark) Zhang, and Tianbing Xu, Clustering on Complex Graphs, Proc. 23th Conference on Artificial Intelligence (AAAI 2008), Chicago, IL, USA, July, 2008, (24% acceptance rate)
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, Mingliang Zhu, Jian Cheng, and Guan Luo, Visual tracking via incremental log-Euclidean Riemannian subspace learning, Proc. IEEE Computer vision and Pattern Recognition, Anchorage, Alaska, USA, June 2008, (27.9% acceptance rate)
Bo Long, Philip S. Yu and Zhongfei (Mark) Zhang, A general model for multiple view unsupervised learning, Proc. the SIAM International Conference on Data Mining, Atlanta, GA, 2008, (14% acceptance rate)
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, and Christos Faloutsos, Semi-supervised learning based on semiparametric regularization, Proc. the SIAM International Conference on Data Mining, Atlanta, GA, 2008, (14% acceptance rate)