时间： 2014年7月2日（星期三）早8:10
        地点：理科楼122室
        报告题目：Development of sparse models for genomic and image data integration   

        Abstract: In this talk, I will present our recent efforts on the development of sparse models for multi-scale and multi-modal genomic and image data integration and analysis. I will show how to use sparse group CCA model to correlate genomic and image data; how to design sparse models (e.g., collaborative low rank regression) for integrating genomic, imaging and biological knowledge; and how to develop a scaled Lp based sparse regression model for feature selection. All these models have found successful applications in imaging genomics, a hot and emerging area in biomedical research.
 
        Biography of the speaker：Dr. Yu-Ping Wang received the BS degree in applied mathematics from Tianjin University, China, in 1990, and the MS degree in computational mathematics and the PhD degree in communications and electronic systems from Xi’an Jiaotong University, China, in 1993 and 1996, respectively. After his graduation, he had visiting positions at the Center for Wavelets, Approximation and Information Processing of the National University of Singapore and Washington University Medical School in St. Louis. From 2000 to 2003, he worked as a senior research engineer at Perceptive Scientific Instruments, Inc., and then Advanced Digital Imaging Research, LLC, Houston, Texas. In the fall of 2003, he returned to academia as an assistant professor of computer science and electrical engineering at the University of Missouri-Kansas City. He is currently an Associate Professor of Biomedical Engineering and Biostatistics & Bioinformatics at Tulane University School of Science and Engineering & School of Public Health and Tropical Medicine. He is also a member of Tulane Center of Bioinformatics and Genomics and Tulane Cancer Center. His research interests have been computer vision, signal processing and machine learning with applications to biomedical imaging and bioinformatics, where he has over 130 peer reviewed publications. He has served on numerous program committees and NSF/NIH review panels, and served as editors for several journals.