mirror of
https://github.com/waveletlab-uestc/waveletlab-uestc.github.io.git
synced 2026-04-03 00:11:53 +08:00
1 line
56 KiB
JavaScript
1 line
56 KiB
JavaScript
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"},38:function(a,e){a.exports="data:image/jpeg;base64,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"),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Jing Zhong Zhang, Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Academician of Chinese Academy of Sciences, Chengdu Computer Applications Institute, Chinese Academy of Sciences")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tJing Zhong Zhang, Professor, Academician of Chinese Academy of Sciences, Computer Scientist, Mathematician, Mathematics Educator. 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He invented the LianXiang method for augmenting the input of Chinese. From 1984 to 1995 he acted as the CTO of ICTC, i.e. The Company of ICT which was renamed as Legend in 1989 and Lenovo recently. He led the development of Legend Chinese System and Legend Series PC, which were the key products of the company and won the first-class prize of the State Award for Scientific and Technological Achievement in 1988 and 1992 respectively. For years he devoted himself to the development of the homegrown core technology as well as the IT industry of China. In 1994 he was elected as the Academician of Chinese Academy of Engineering. He was rewarded the Lifetime Achievement Award by the Chinese Information Processing Society of China (CIPS) and China Computer Federation (CCF) in 2011 and 2015 respectively.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(39),alt:"tangyuanyan"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Yuan Yan Tang, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tYuan Yan Tang is a Chair Professor in Faculty of Science and Technology at University of Macau and Professor/Adjunct Professor/Honorary Professor at several institutes in China, USA, Canada, France, and Hong Kong. His current interests include wavelets, pattern recognition, image processing, and artificial intelligence. He has published more than 400 academic papers and is the author/coauthor of over 25 monographs/books/bookchapters. He is the Founder and Editor-in-Chief of International Journal on Wavelets, Multiresolution, and Information Processing (IJWMIP), and Associate Editors of several international journals. He is the Founder and Chair of pattern recognition committee in IEEE SMC. He has serviced as general chair, program chair, and committee member for many international conferences. Dr. Tang is the Founder and General Chair of the series International Conferences on Wavelets Analysis and Pattern Recognition (ICWAPRs). He is the Founder and Chair of the Macau Branch of International Associate of Pattern Recognition (IAPR). Dr. Y. Y. Tang is a Fellow of IEEE, and Fellow of IAPR.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(40),alt:"lijianping"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Jian Ping Li, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("International Centre for Wavelet Analysis and Its applications,Big Data Research Institute, School of Computer Science,University of Electronic Science and Technology of China(UESTC)")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tProfessor Dr. Jian Ping Li, male, born on October 11,1964. He received the B.S. degree in applied mathematics from Chongqing University, Chongqing, China, in 1986, the M. Eng. degree in software engineering and M. Sci. degree in computational mathematics from the Graduate School of Xi'an Jiaotong University, Xi'an, Shanxi, China, in 1989, and the Ph.D. degree in computer science from the Graduate School of Chongqing University, Chongqing, China, in 1998. From 1999 to 2000, he was a post doctoral and visiting professor working at Hong Kong Baptist University under the leadership of Professor Dr. Yuan Yan Tang. From 2002 to 2003, 2005 to 2006, and in 2010, 2011, 2013, 2014, 2015,he was a senior visiting professor working respectively at Provence University, France, University of Guelph, Canada, Washington University, USA, University of Zurich, Switzerland. He is presently a Professor in International Centre for Wavelets Analysis and Its Applications (ICWAA) of University of Electronic Science and Technology of China(UESTC), Chengdu, China, and as a head of ICWAA, he is the dean of Big Data Research Institute of UESTC. Dr. Li has served as a Syndic for Awards of National Science and Technology of China, a founder of the International Journal on Multiresolution, Wavelets, Applications (IJMWA), a founder and Editor in Chief of International Progress on Wavelet Active Media Technology and Information Processing, and also as General Chairman of many international conferences, a reviewer for many international famous Journals. His book Wavelet Analysis & Signal Processing: Theory, Applications & Software Implementations, was awarded the second prize of National Science and Technology of China (1999), and it is very important reference for many scientists. Dr. Li has published more than 300 technical papers and is the author/ co-author of 30 books on subjects ranging from wavelet analysis and its applications to computer science. His current interests include wavelet theory and applications, fractal, image processing, pattern recognition, information security, big data, artificial intelligence.\n\t\t")])])])])},[],!1,null,null,null);"function"==typeof i&&i(r);e.default=r.exports}}]); |