Ph.D. Electrical and Computer Engineering, University of Illinois Urbana-Champaign
Current Research Interests:
Signal and image processing, statistical learning theory, biomedical and healthcare informatics, and their applications.
Dr. Cheng's research interests include Feature extraction and selection from high-dimensional and/or large scale dataset; correlation clustering; optimal configuration on graphs; efficient/optimal representation for high-dimensional data and massive data for acquisition, transmission, visualization, and classification; signal/image processing and pattern recognition problems in biomedicine, engineering, healthcare, etc. He worked on multimedia information forensics, security, and pattern recognition. His current research focuses mainly on biomedical information/image processing. Due to the extensive use of medical images for disease prognosis and diagnosis, and health promotion in healthcare and biomedicine, biomedical imaging/processing and bioinformatics become increasingly important. The research questions include how to fuse multiple image modalities and data sources to promote early diagnosis and improve the accuracy, how to represent and transmit huge amount of medical information, and how to extract the most salient information or obtain the sparse representations from large data set, etc. He studies these issues by using computer techniques including machine learning and signal/image processing.
- "A sparse learning machine for high-dimensional data with applications to microarray gene analysis," Q. Cheng, in press, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
- "A novel distributed sensor positioning system using the dual of target tracking," L. Zhang, Q. Cheng, L. Wang, and S. Zeadali, IEEE Trans. Computers, vol. 57, no. 2, pp. 246-260, Feb. 2008.
- "Generalized embedding of multiplicative watermarks," Qiang Cheng, in press, IEEE Trans. Circuit and Systems for Video Technology.