Biosketch
Dr. Shijun Wang received his PhD degree in Control Science and Engineering from Tsinghua University, China, where his research focused on machine learning and complex systems. He earned a BS in Electronic Engineering at Beihang University and an MS in Communication at Second Aerospace Science Academy, China. Dr. Shijun Wang's current research interests in the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory include machine learning, statistical image analysis and their applications in computer aided diagnosis. He is an associate editor of Medical Physics and reviewer for IEEE TMI, IEEE TBME, Journal of Artificial Intelligence Research, Journal of Magnetic Resonance Imaging, Medical Physics, Pattern Analysis & Applications, and Journal of Theoretical Biology.
Honors and Awards
Fellows Award for Research Excellence (FARE) 2009 competition, National Institutes of Health.
Fellows Award for Research Excellence (FARE) 2010 competition, National Institutes of Health.
Selected Publications
BOOK CHAPTERS
Wang S, and Zhang C, Learning on Complex Networks. In Zhou ZH and Wang J (Eds.) Machine Learning and Its Applications 2007, Tsinghua University Press, Beijing, China.
JOURNAL ARTICLES
Nguyen T, Wang S, Anugu V, Rose N, Burns J, McKenna M, Petrick N, and Summers RM. Distributed Human Intelligence for Colonic Polyp Classification in Computer-aided Detection for CT Colonography. To be published on Radiology.
Linguraru MG, Wang S, Shah F, Gautam R, Peterson J, Linehan MW, Summers RM. Automated noninvasive classification of renal cancer on multiphase CT. Medical Physics, vol. 38 (10), pp. 5738-5746, 2011.
Wang S, Yao J, Petrick N, and Summers RM. Combining Statistical and Geometric Features for Colonic Polyp Detection in CTC Based on Multiple Kernel Learning. International Journal of Computational Intelligence and Applications (IJCIA), Vol. 9(1), pp. 1-15, 2010.
Wang S, and Zhang C. Collaborative Learning by Boosting in Distributed Environments. The International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Vol. 24(5), pp. 763-789, 2010.
Wang S, Yao J, Liu J, Petrick N, Van Uitert RL, Periaswamy S, and Summers RM. Registration of prone and supine CT Colonography scans using correlation optimized warping and canonical correlation analysis. Medical Physics, Vol. 36(12), pp. 5595-5603, 2009.
Zhang C and Wang S, Boosting Learning on Classifier Network. Communications of the China Computer Federation, Vol. 8, 2009.
Wang S, Yao J and Summers RM. Improved Classifier for Computer-aided Polyp Detection in CT Colonography by Nonlinear Dimensionality Reduction. Medical Physics, Vol. 35(4), pp. 1377-1386, 2008.
Wang S, Szalay MS, Zhang C, and Csermely P. Learning and Innovative Elements of Strategy Adoption Rules Expand Cooperative Network Topologies. PLoS ONE 3(4): e1917. doi:10.1371/journal.pone.0001917, 2008.
Wang S, Kou Z, and Zhang C. Network Boosting on Different Networks. Physica A: Statistical Mechanics and its Applications, Vol. 366, pp. 561-570, 2006.
Wang S, and Zhang C. Microscopic Model of Financial Markets Based on Belief Propagation. Physica A: Statistical Mechanics and its Applications, Vol. 354C, pp. 496-504, 2005.
Wang S, and Zhang C. Weighted Competition Scale-Free Network. Physical Review E 70, 066127, 2004.
PEER REVIEWED CONFERENCE PAPERS
Wang S, Anugu V, Nguyen T, Rose N, Burns J, McKenna M, Petrick N, and Summers RM. Fusion of Machine Intelligence and Human Intelligence for Colonic Polyp Detection in CT Colonography. 2011 IEEE International Symposium on Biomedical Imaging (ISBI), 2011.
Wang S, Petrick N, Van Uitert RL, Periaswamy S, and Summers RM. Graph Matching Based on Mean Field Theory. International Conference on Image Processing (ICIP), 2010.
Wang S, Yao J, Liu J, Petrick N, and Summers RM. Centerline registration of prone and supine CT Colonography scans based on correlation optimized warping and anatomical landmarks. 2009 IEEE International Symposium on Biomedical Imaging (ISBI), Boston, Massachusetts, 2009.
Wang S, Summers RM and Zhang C. A Fast Mean-field Method for Large-scale High-dimensional data and its Application in Colonic Polyp Detection at CT Colonography, International Joint Conference on Neural Networks (IJCNN), Atlanta, Georgia, 2009.
Wang S, Yao J, and Summers RM. Matching Colonic Polyps from Prone and Supine CT Colonography Scans Based on Statistical Curvature Information. The International Conference on Pattern Recognition (ICPR), Tampa, Florida, 2008.
Wang F, Wang S, Zhang C and Winther O. Semi-supervised Mean Fields. The Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS), San Juan, Puerto Rico, 2007.
Wang S, and Zhang C. Network Game and Boosting. The 16th European Conference on Machine Learning (ECML), Springer-Verlag, Vol. 3720 / 2005, pp. 461-472,Porto, Portugal, 2005.
Zhang Y, Zhang C, and Wang S. Clustering in Knowledge Embedded Space. The 14th European Conference on Machine Learning (ECML), Lecture Notes in Artificial Intelligence (LNAI), Springer-Verlag, Vol. 2837 / 2003, pp. 480-491, 2003.
