Ching Y Suen
Director
Pattern Recongintion
CDBIO
Canada
Biography
Dr. Ching Y. Suen is the Director of CENPARMI and the Concordia 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. Prof. Suen has served at numerous national and international professional societies as President, Vice-President, Governor, and Director. He has given 45 invited/keynote papers at conferences and 195 invited talks at various industries and academic institutions around the world. He has been the Principal Investigator or Consultant of 30 industrial projects. His research projects have been funded by the ENCS Faculty and the Distinguished Chair Programs at Concordia University, FCAR (Quebec), NSERC (Canada), the National Networks of Centres of Excellence (Canada), the Canadian Foundation for Innovation, and the industrial sectors in various countries, including Canada, France, Japan, Italy, and the United States. Dr. Suen has published 4 conference proceedings, 12 books and more than 495 papers, and many of them have been widely cited while the ideas in others have been applied in practical environments involving handwriting recognition, thinning methodologies, and multiple classifiers. Dr. Suen is the recipient of numerous awards, including the Gold Medal from the University of Bari (Italy 2012), the IAPR ICDAR Award (2005), the ITAC/NSERC national award (1992), and the \\\"Concordia Lifetime Research Achievement\\\" and \\\"Concordia Fellow\\\" Awards (2008 and 1998 respectively). 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 Editor-in-Chief of the journal of Pattern Recognition and an Adviser or Associate Editor of 5 journals.
Research Interest
Computational linguistics Computer analysis and recognition of documents
