Plenary Speakers

Plenary Speakers SOCO'12

Ponnuthurai Nagaratnam Suganthan

Ponnuthurai Nagaratnam Suganthan received the B.A degree, Postgraduate Certificate and M.A degree in Electrical and Information Engineering from the University of Cambridge, UK in 1990, 1992 and 1994, respectively. He obtained his Ph.D. degree from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He was a predoctoral Research Assistant in the Dept of Electrical Engineering, University of Sydney in 1995–96 and a lecturer in the Dept of Computer Science and Electrical Engineering, University of Queensland in 1996–99. Since 1999 he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore where he was an Assistant Professor and now is an Associate Professor. He is an Editorial Board Member of the Evolutionary Computation Journal, MIT Press. He is an associate editor of the IEEE Trans on Evolutionary Computation, Information Sciences (Elsevier), Pattern Recognition (Elsevier) and Int. J. of Swarm Intelligence Research Journals. He is a founding co-editor-in-chief of Swarm and Evolutionary Computation, an Elsevier Journal. SaDE (April 2009) paper won "IEEE Trans. on Evolutionary Computation" outstanding paper award. His research interests include evolutionary computation, pattern recognition, multi-objective evolutionary algorithms, bioinformatics, applications of evolutionary computation and neural networks. His publications have been well cited (Googlescholar Citations). He is a Senior Member of the IEEE.

googlescholar citations

Jeng-Shyang Pan

Jeng-Shyang Pan received the B. S. degree in Electronic Engineering from the National Taiwan University of Science and Technology in 1986, the M. S. degree in Communication Engineering from the National Chiao Tung University, Taiwan in 1988, and the Ph.D. degree in Electrical Engineering from the University of Edinburgh, U.K. in 1996. Currently, he is the Doctoral advisor in Harbin Institute of Technology and Professor in the Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Taiwan. He has published more than 400 papers in which 110 papers are indexed by SCI. He is the IET Fellow, UK and the Tainan Chapter Chair of IEEE Signal Processing Society. He was Awarded Gold Prize in the International Micro Mechanisms Contest held in Tokyo, Japan in 2010. He was also awarded Gold Medal in the Pittsburgh Invention & New Product Exposition (INPEX) in 2010, Gold Medal in the International Exhibition of Geneva Inventions in 2011 and Gold Medal of the IENA, International “Ideas – Inventions – New products“, Nuremberg, Germany. He was offered Thousand-Elite-Project in China. He is on the editorial board of International Journal of Innovative Computing, Information and Control, LNCS Transactions on Data Hiding and Multimedia Security, and Journal of Information Hiding and Multimedia Signal Processing. His current research interests include soft computing, robot vision and cloud computing.

Bio-inspired Information Hiding

With the widespread use of Internet and wireless networks, and the blooming growth in consumer electronic devices and advances in multimedia compression techniques, multimedia streams are easily acquired nowadays. Hence, how to achieve copyright protection of the above-mentioned multimedia contents, and how to effectively hide additional data into such digital contents as another means for protecting the intellectual property, has become an important issue.

People learn a lot from Mother Nature. Applying the analogy to biological systems, we are able to handle the challenges in the algorithm and application for information hiding. As we know, there are several parameters that need to be carefully selected when designing an information hiding algorithm. These parameters, to cite some, include: the quality of the multimedia content with hidden data embedded, the number of bits that can be hidden, the security for delivering the multimedia content, and the capability to withstand the intentional or unintentional signal processing, called attacks. These parameters have their own limitations, and they might have conflict to one another. For instance, hiding more bits into the digital contents may degrade the perceptual quality to some extent. Based on this observation, bio-inspired optimization techniques, including evolutionary algorithms (EA) and neural networks (NN), are employed to help solve the problem relating to information hiding.

Marios M. Polycarpou

Marios M. Polycarpou, Professor, Ph.D, IEEE Fellow
Department of Electrical and Computer Engineering, University of Cyprus, Cyprus

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