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ZHANG Bing Wins Support from National Talents Program
 
 Date: 2015-02-09  Page Views:
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Prof. ZHANG Bing has recently received an award from the National Hundred, Thousand, and Ten Thousand Talents Program in 2014 and honored as an Outstanding Young and Middle-aged Expert.

Under the joint auspices of the Ministry of Human Resources and Social Security and eight other governmental departments, the Program is aimed at developing a team of world-class S&T professionals with focus on innovative talents working at R&D frontlines. A total of 390 people won its support in 2014.  

Prof. Zhang, Deputy Director of RADI and director of the CAS Key Lab of Digital Earth Science, is specialized in hyperspectral remote sensing with about 20 years of experience and also simultaneously began to focus on Digital Earth in recent years. His research interests include development of physics-based models and image processing software for the use of hyperspectral remote sensing data in solving problems in various contexts. He has authored or co-authored around 150 publications, including more than 100 JCR journal papers and more than 50 peer-reviewed international conference papers. He has written 4 books especially in hyperspectral remote sensing area, which serve as the main materials for education and research in China. He has coordinated many national-level projects supported by a variety of S&T programs in China. In the past ten years, he has received 8 Chinese National, Ministerial and Provincial S&T Progress Awards in total. Prof. Zhang has had a variety of editorial responsibilities in international journals and conferences. He is a Senior Member of IEEE and an Associate Editor of the IEEE Journal of Selected Topics in Applied Earth Observations in Remote Sensing (JSTARS), and also the technical committee member of Workshop on Hyperspectral Image and Signal Processing (WHISPERS). He has been guest editor of several special issues, including a JSTARS special issue on Hyperspectral Remote Sensing: Theory, Methods, and Applications, or a JSTARS special issue on Big Data in Remote Sensing, among others.

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