Keynote Speeches

The computer technologies have grown significantly in the past years. More and more multimedia products such as digital cameras have become popular, so digital images are shared and transmitted widely over Internet. However, transmitting secret or important images, such as military or commercial images, over Internet is very dangerous. Malicious users may monitor Internet and try to eavesdrop these valuable images. To protect these images, visual cryptography is necessary for secure communications over Internet. Herein, secret image sharing can be applied to achieve the goal of visual cryptography. In this speech, I will talk about some visual cryptosystems based on the concept of secret image sharing.
Also, I'll talk about the concept of designing an authenticatable visual secret sharing. As for the topic of secret image sharing, the secret image sharing scheme uses several noise-like images, called shadows, to replace the original image transmitting over the Internet. The shadows can avoid threats from the illegal persons to access the secret image directly.
Secret image sharing techniques were proposed to be another branch outside traditional cryptographic techniques and steganography. Based on sharing secret images, visual cryptography for binary images, grayscale images and color images will be introduced.

Professor C. C. Chang was born in Taichung, Taiwan on Nov. 12th, 1954. He obtained his Ph.D. degree in computer engineering from National Chiao Tung University. He's first degree is Bachelor of Science in Applied Mathematics and master degree is Master of Science in computer and decision sciences. Both were awarded in National Tsing Hua University. Dr. Chang served in National Chung Cheng University from 1989 to 2005. His current title is Chair Professor in Department of Information Engineering and Computer Science, Feng Chia University, from Feb. 2005.

Prior to joining Feng Chia University, Professor Chang was an associate professor in Chiao Tung University, professor in National Chung Hsing University, chair professor in National Chung Cheng University. He had also been Visiting Researcher and Visiting Scientist to Tokyo University and Kyoto University, Japan. During his service in Chung Cheng, Professor Chang served as Chairman of the Institute of Computer Science and Information Engineering, Dean of College of Engineering, Provost and then Acting President of Chung Cheng University and Director of Advisory Office in Ministry of Education, Taiwan.

Professor Chang's specialties include, but not limited to, data engineering, database systems, computer cryptography and information security. A researcher of acclaimed and distinguished services and contributions to his country and advancing human knowledge in the field of information science, Professor Chang has won many research awards and honorary positions by and in prestigious organizations both nationally and internationally. He is currently a Fellow of IEEE and a Fellow of IEE, UK. And since his early years of career development, he consecutively won Outstanding Youth Award of the R. O. C., Outstanding Talent in Information Sciences of the R. O. C., AceR Dragon Award of the Ten Most Outstanding Talents, Outstanding Scholar Award of the R. O. C., Outstanding Engineering Professor Award of the R. O. C., Chung-Shan Academic Publication Awards, Distinguished Research Awards of National Science Council of the R. O. C., Outstanding Scholarly Contribution Award of the International Institute for Advanced Studies in Systems Research and Cybernetics, Top Fifteen Scholars in Systems and Software Engineering of the Journal of Systems and Software, and so on. On numerous occasions, he was invited to serve as Visiting Professor, Chair Professor, Honorary Professor, Honorary Director, Honorary Chairman, Distinguished Alumnus, Distinguished Researcher, Research Fellow by universities and research institutes. He also published over 990 papers in Information Sciences. In the meantime, he participates actively in international academic organizations and performs advisory work to government agencies and academic organizations.

What can Computing Machines do better than human beings? The jobs that require "massive" computing resources! But what are we going to "teach" a machine if we human beings do not know how to do a job?
Examples of such "subjective" jobs can be human face recognition, start codon prediction, and etc. There is a gap between our expectation on computing performances and our knowledge on how to do the job. This talk argues that the objective of high accuracy in related research for such jobs leads to nowhere but a general "trial and error" process; and shows by evidence that the current advance in face recognition has indeed not provided a significantly better solution than a trivial pixel matching based method. Therefore, the goal in developing AI algorithms should be shifted from "accuracy" to "stability" so that theoretical rather than fully experimental research can be carried out.

Professor Liang Chen (http://web.unbc.ca/~chenl/) received his PhD in Computer Science from Institute of Software, Chinese Academy of Sciences (Academia Sinica), China, in 1994. He is currently professor of computer science and professor on interdisciplinary program at University of Northern British Columbia (UNBC), BC, Canada. He was the former Chair of Computer Science Department at UNBC. Before coming to Canada in 2001, he spent time in China, France and Japan. Dr. Chen's research areas include pattern recognition, intelligent language tutoring system, and the computational intelligence fields.
Dr. Chen is currently chairing the IEEE Subsection of Northern British Columbia.

The development of information systems, especially the explosive growth of Internet and World Wide Web has led to irreversible changes in our life. We are now facing rich and colorful information sources that we could not imagine a decade ago. However, the amount of information is increasing faster than our processing ability, thus evaluating all these alternatives and then making choice becomes infeasible. This information overload problem asks for automatic techniques on information filtering. This presentation will discuss the information filtering problems in large-scale social networks. I will start with the simplest yet the most fundamental information filtering problems: ranking and predicting. Then I will summarize our recent efforts on the personalized recommendation. Finally, I will discuss what the differences between the current- and the next-generation recommender systems are.

Tao Zhou received his Bachelor's degree from the University of Science and Technology of China in 2005. He obtained his Ph. D. majoring theoretical physics from the University of Fribourg in 2010. In March 2010, he was awarded a full professor position in the University of Electronic Science and Technology of China. His main research interests include infophysics, complex networks and human dynamics. He has published more than 110 SCI journal papers, and about 50 papers have been published in prestigious journals, including PNAS, Physical Reviews, New Journal of Physics and Europhysics Letters. Reports on his works appeared in many mainstream academic media, including Nature News, PNAS News, My Science, PhysOrg, TG Daily, Dutch Science Magazine, L¡¦Atelie, etc. All his publications have received more than 1200 citations according to the Web of Science, and his H-index is equal to 18. He is an editor or guest editor of many scientific journals, including Physics Procedia, Journal of Computer Science and Technology, Journal of Electronic Science and Technology, etc, and a standing referee of more than 20 SCI journals. He was awarded the 2010 Chorafas Prize for Young Scientists (19 young scientists over the world has obtained this prize in 2010), the first prize for Natural Science Progress by Chinese Education Ministry in 2009, and the first prize for Natural Science Progress by Anhui Province in 2009.