Professor Meng Joo Er
Nanyang Technological University, Singapore
Professor Er Meng Joo is currently a Full Professor in
Electrical and Electronic Engineering, Nanyang Technological University,
Singapore. He served as the Founding Director of Renaissance Engineering
Programme and an elected member of the NTU Advisory Board from 2009 to 2012.
Furthermore, he served as a member of the NTU Senate Steering Committee from
2010 to 2012.
He has authored five books entitled "Dynamic Fuzzy Neural Networks: Architectures, Algorithms and Applications" and "Engineering Mathematics with Real-World Applications" published by McGraw Hill in 2003 and 2005 respectively, and "Theory and Novel Applications of Machine Learning" published by In-Tech in 2009, "New Trends in Technology: Control, Management, Computational Intelligence and Network Systems" and "New Trends in Technology: Devices, Computer, Communication and Industrial Systems", both published by SCIYO, 18 book chapters and more than 500 refereed journal and conference papers in his research areas of interest.
Professor Er was bestowed the Web of Science Top 1 % Best Cited Paper and the Elsevier Top 20 Best Cited Paper Award in 2007 and 2008 respectively. In recognition of the significant and impactful contributions to Singapore's development by his research projects, Professor Er won the Institution of Engineers, Singapore (IES) Prestigious Engineering Achievement Award twice (2011 and 2015). He is also the only dual winner in Singapore IES Prestigious Publication Award in Application (1996) and IES Prestigious Publication Award in Theory (2001). Under his leadership, the NTU Team emerged first runner-up in the Freescale Technology Forum Design Challenge 2008. He received the Teacher of the Year Award for the School of EEE in 1999, School of EEE Year 2 Teaching Excellence Award in 2008, the Most Zealous Professor of the Year Award in 2009 and the Outstanding Mentor Award in 2014. He also received the Best Session Presentation Award at the World Congress on Computational Intelligence in 2006 and the Best Presentation Award at the International Symposium on Extreme Learning Machine 2012. On top of this, he has more than 50 awards received at international and local competitions.
Currently, Professor Er serves as the Editor-in-Chief of Transactions on Machine Learning and Artificial Intelligence and the International Journal of Electrical and Electronic Engineering and Telecommunications. He also serves an Area Editor of International Journal of Intelligent Systems Science and an Associate Editor of 14 refereed international journals, namely IEEE Transaction on Cybernetics, Information Sciences, Neurocomputing, Asian Journal of Control, International Journal of Fuzzy Systems, ETRI Journal, International Journal of Humanoid Robots, International Journal of Modelling, Simulation and Scientific Computing, International Journal of Applied Computational Intelligence and Soft Computing, International Journal of Business Intelligence and Data Mining, International Journal of Fuzzy and Uncertain Systems, International Journal of Automation and Smart Technology, International Journal of Intelligent Information Processing and an editorial board member of the Open Automation and Control Systems Journal and the EE Times.
Professor Er has been invited to deliver more than 60 keynote speeches and invited talks overseas. He has also been active in professional bodies. He has served as Chairman of IEEE Computational Intelligence Society (CIS) Singapore Chapter (2009 to 2011) and Chairman of IES Electrical and Electronic Engineering Technical Committee (EEETC) (2004 to 2006 and 2008 to 2012). Under his leadership, the IEEE CIS Singapore Chapter won the CIS Outstanding Chapter Award 2012 (The Singapore Chapter is the first chapter in Asia to win the award). In recognition of his outstanding contributions to professional bodies, he was bestowed the IEEE Outstanding Volunteer Award (Singapore Section) and the IES Silver Medal in 2011. Due to his outstanding contributions in education, research, administration and professional services, he is listed in Who's Who in Engineering, Singapore, Edition 2013.
Professor Jiankun Hu
School of Engineering and Information Technology, UNSW Canberra (Australian Defence Force Academy), Australia
Jiankun Hu is full Professor at the School of Engineering and
IT, University of New South Wales, Canberra, Australia. He has obtained his BE
from Hunan University, China in 1983; PhD in Control Engineering from Harbin
Institute of Technology, China in 1993 and Masters by Research in Computer
Science and Software Engineering from Monash University, Australia in 2000. He
has worked in Ruhr University Germany on the prestigious German Alexander von
Humboldt Fellowship 1995-1996; research fellow in Delft University of the
Netherlands 1997-1998, and research fellow in Melbourne University, Australia
1998-1999. Jiankun's main research interest is in the field of cyber security
including Image Processing/Forensics and machine learning where he has published
many papers in high-quality conferences and journals including IEEE Transactions
on Pattern Analysis and Machine Intelligence (PAMI). He has served in the
editorial board of up to 7 international journals including IEEE transactions on
Information Forensics and Security. He also served as Security Symposium Chair
of IEEE flagship conferences of IEEE ICC and IEEE Globecom. He has obtained 7
ARC (Australian Research Council) Grants and has served at the prestigious Panel
of Mathematics, Information and Computing Sciences (MIC), ARC ERA (The
Excellence in Research for Australia) Evaluation Committee.
Abstract: Biometrics security mechanism such as fingerprint, face, and iris etc. can address the built-in weakness of traditional cryptography. However, biometrics templates themselves need to be protected. With the increasing the use of biometrics, there is a trend to store biometrics in the cloud. Obviously these biometrics data needs to encrypted in the cloud for privacy protection. Therefore there is a strong demand for privacy-preserving biometrics authentication over these encrypted data. The powerful homomorphic encryption can process mirror operations between encrypted and unencrypted domains. However, a direct application of this method is problematic as it will inove intensive computation and also it cannot address the problem of biometrics matching. This talk will introduce latest development in the field and propose a solution.
Professor Nicolas H. Younan
Mississippi State University, USA
Nicolas H. Younan is currently the Department Head and James Worth Bagley Chair of Electrical and Computer Engineering at Mississippi State University. He received the B.S. and M.S. degrees from Mississippi State University, in 1982 and 1984, respectively, and the Ph.D. degree from Ohio University in 1988. Dr. Younan's research interests include signal processing and pattern recognition. He has been involved in the development of advanced signal processing and pattern recognition algorithms for data mining, data fusion, feature extraction and classification, and automatic target recognition/identification. He has published over 250 papers in refereed journals and conference proceedings, and book chapters. He served as the General Chair and Editor for the 4th IASTED International Conference on Signal and Image Processing, Co-Editor for the 3rd International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Guest Editor - Pattern Recognition Letters and JSTARS, and Co-Chair - Workshop on Pattern Recognition for Remote sensing (2008-2010).
Abstract: Earth Observations (EO) data are obtained from a multitude of sources and requires tremendous efforts and coordination among researchers and user groups to come to a shared understanding on a set of concepts involved in a domain. The ultimate goal of any EO system is to provide understanding, which will often require expertise and/or data sources from globally distributed resources, thus presenting unique challenges. To address these challenges, it is incumbent upon the global community to evolve and sustain a global observation network. These observations serve as the foundation for the models that are used to describe Earth processes. As this observational data accumulates in global archives, new opportunities become available for knowledge discovery about the Earth system. However, access to these observational data is optimized for the science teams for whom the instruments were launched and access by operational users may be problematic. This presentation will lay out some of the challenges for those engineers and scientists involved in pattern recognition in the Earth remote sensing arena. It describes the problem space for making decisions and introduces the concept of contextual remote sensing.
Professor E. Baburaj
Department of Computer Science and Engineering, Marian Engineering College, India
Prof. Baburaj is associated with Marian Engineering College; Trivandrum, India. He is an experienced academician having 24 years of teaching experience. His areas of interests are; Wireless Sensor Networks and Network Security. He is actively engaged in Research & Development activities & has obtained grants from AICTE and ISTE for doing research projects in the area of Wireless Sensor Networks. He has presented number of papers and has delivered many Science and Technical lectures in National & International Conferences & Seminars. Five scholars have completed Ph.D under his Supervision. He has published more than 100 research publications of high repute and has written a book. Baburaj graduated from Madurai Kamaraj University in the year 1992 and did his M.E., degree from Madurai Kamaraj University in 2002. He passed his M.S. Software systems from BITS, Pilani in the year 1998. He obtained Ph.D. in the Dept. of Computer Science and Engineering in from Anna University, Chennai in 2009.
Abstract: Steganography is a kind of security technique that conceals the presence of message between sender and intended recipient. Recently, many steganographic methods are designed for embedding secrete message into an image. The algorithms like Steganography-based Information Hiding (SIH) approach with Lifting Wavelet Transform (LWT) and Variable Step Size Firefly Algorithm (VSSFA) outperforms the number of algorithms and improves the security of data hiding. These hybrid approaches provide higher embedding capacity, security and quality of stego image with optimal LWT and diminish the computational complexity and to enhance the robustness of data hiding and supports random distribution of secret information. This talk will present the novel methods and latest developments in this focused area of research.
Professor Yoshifumi Manabe
Faculty of Informatics, Kogakuin University, Tokyo, Japan
Yoshifumi Manabe was born in 1960. He received his B.E., M.E., and Dr.E. degrees from Osaka University, Osaka, Japan, in 1983, 1985, and 1993, respectively. From 1985 to 2013, he worked for Nippon Telegraph and Telephone Corporation. From 2001 to 2013, he was a guest associate professor of Graduate School of Informatics, Kyoto University. Since 2013, he has been a professor of the Faculty of Informatics, Kogakuin University, Tokyo, Japan. His research interests include distributed algorithms, cryptography, game theory, and graph theory. Dr. Manabe is a member of ACM, IEEE, IEICE, IPSJ, and JSIAM.
Abstract: Fair division problem is one of essential problems in our daily life. It can be used in cutting a cake, determining the borders in an international dispute, and so on. This talk discusses the case of divisible goods. The envy-freeness is considered to be the most important criteria to be satisfied. Many envy-free cake-cutting protocols have been considered. However, envy-freeness does not imply true fairness. The talk discusses the problem and how true fairness can be achieved.