Prof. Ching Yee Suen
Concordia University, Canada
IEEE Life Fellow, RSC Fellow, IAPR Fellow
Research Areas: Pattern recognition, image processing, AI, machine learning, and applications; Handwriting analysis, font design, computational linguistics, and personality studies
Brief Introduction: Dr. Ching Y. Suen is the Founder and Co-Director of CENPARMI and the Concordia Honorary Chair on AI & Pattern Recognition. He received his Ph.D. degree from UBC Vancouver) and his Master's degree from the University of Hong Kong. He has served as the Chairman of the Department of Computer Science and as the Associate Dean (Research) of the Faculty of Engineering and Computer Science of Concordia University. He is the chief architect and donor of the CENPARMI Scholarship of Concordia. Prof. Suen has supervised 130 doctoral and master's students to completion, and guided/hosted 100 long-term visiting scientists and professors. He is a fellow of the IEEE (since 1986), IAPR (1994), and the Academy of Sciences of the Royal Society of Canada (1995). Currently, he is the Emeritus Editor-in-Chief of the journal of Pattern Recognition, an Adviser or Associate Editor of 5 other journals, and Editor of a new book series on Language Processing and Pattern Recognition. Actually he has held previous positions as Editor-in-Chief, or Associate Editor or Adviser of 6 other journals. He is not only the founder of four conferences: ICDAR, IWFHR/ICFHR, ICPRAI, and VI, but has also organized more than 12 international conferences including ICPR, ICDAR, ICFHR, ICPRAI, ICCPOL, and as Honorary Chair of numerous international conferences. In 1997, he created the IAPR ICDAR Awards, to honour both young and established outstanding researchers in the field of Document Analysis and Recognition. He has always been fascinated by letters and characters, ever since he started his doctoral research on teaching the computer to read multi-font documents with a voice output for the blind.
Prof. Qiong Wang
Peking University, China
Research Areas: MOOCs Instructional Design and Data Analysis, e-learning Environment and Teaching Methods, Intelligent Teaching System, Teacher Professional Development Network Community, Educational technology Theory and research methods
Brief Introduction: Qiong Wang graduated from the Department of Computer Science and Technology of Peking University and received his Doctor of Science degree from Peking University. Professor of educational technology. Her research interests include basic theories and research methods of educational technology, E-1eaming learning environment and instructional design, development strategies of teaching informatization at all levels, design of various adult training, and evaluation of educational informatization projects. She has presided over and participated in more than 50 scientific research projects of the Ministry of Education and Beijing. Since 1998, as a key member of the Ministry of Education, participated in a number of educational informatization strategic planning research. She served as the core education expert in several cooperation projects between the Ministry of Education of China and internationally renowned IT manufacturers (Intel, Microsoft, Apple, Dell). She has published four monographs and two translated books, edited three sets of teacher training textbooks, and published more than 50 academic papers. The national network teacher training course on teachers' educational technology Competence (intermediate level), which he presided over and developed, has trained more than 300,000 teachers. Developed and implemented the first MOOC course for teacher training in China. The first batch registered 25,000 people and the completion rate was 20%, which was welcomed by frontline teachers.
Prof. Zhihai He
Southern University of Science and Technology, China
IEEE Fellow
Research Areas: Intelligent cyber-physical systems, machine learning, computer vision, wireless sensor networks, embedded multimedia system design, image/video compression
Brief Introduction: He was a tenured full professor and Robert Lee Tatum Distinguished Chair Professor in the Department of Electrical Engineering at the University of Missouri for 18 years. During his work in the United States, he undertook more than ten key research projects of the National Science Foundation (NSF) and the National Institutes of Health (NIH). His current research interests are deep learning, machine vision, artificial Intelligence Internet of Things (AIoT). Named to Stanford University's World's Top 2% Scientists' Lifetime Science Impact List and the 2019 Science Impact List. Professor He has served as editorial board editor of several international journals, including IEEE Transactions on Circuits and Systems for Video Technologies; IEEE Transactions on Multimedia and Journal of Visual Communication and Image Representation. He is a co-chair of the 2007 International Wireless Multimedia Conference, a member of the IEEE Video Processing Technical Committee, a member of the IEEE Multimedia Technical Committee, and a sub-chair of several international conferences. He has published more than 150 papers in top international journals and conferences. His main research achievements include: establishing the unified rate control model of image and video compression communication system; Firstly, Shannon Rate-distortion (R-D) model in information theory is extended to energy domain (P), and P-R-D model is established for energy consumption optimization of mobile video equipment. Vision sensor network was first proposed and studied.