Keynote Speakers

	Prof. Bebo White Stanford University, USA
Title:
The Future of Online Social Networking - Opportunities and Challenges
Abstract: Online social networks are revolutionizing basic human social interaction ¨C from enterprise business applications to expanded learning environments to friend/interest-based networks and beyond. There is every indication that participation in these networks will continue to grow exponentially for years into the future. While new applications to support innovative modes of online social networking continue to be introduced, it is evident that this remarkable phenomenon is due to far more that just technology. Despite their fairly simple concept, online social networks represent a complex array of privacy, legal, ethical, cultural, and administrative issues. With these issues come challenges that must be addressed in future network applications in order to assure their adoption and overall benefit. In this talk, I¡¯ll provide an overview of the current social networking landscape and describe the existing issues and challenges. I will then attempt to offer solutions to these challenges and speculate on what social networks will look like in the next decade and how we will be using them. Resume: Bebo White is a Departmental Associate (Emeritus) at the SLAC National Accelerator Center at Stanford University. In addition he holds faculty positions at the University of San Francisco and Hong Kong University. His research interests include Internet and World Wide Web applications and technologies, network and applications security, human-computer interaction, social networking applications, and Web Science, computational high-energy physics, high performance computing. Prof. White is the author (or co-author) of seven books and numerous refereed journal and conference papers. His work has led to frequent speaking engagements at international conferences and seminars. Prof. White first became involved with the World Wide Web while at CERN in Geneva 1988-89. Upon his return he was a part of the team establishing the first US Web site (the fifth in the world) at SLAC. He is on the advisory board of the Web History Center, and has been a member of the International World Wide Web Conferences Steering Committee (IW3C2) since 1996 and served as general co-chair 1996 and 2003. Prof. White is a founding member of the International Society for Web Engineering (ISWE) and the International Conference on Web Engineering (ICWE) series, general chair of ICWE 2009. His is managing editor of the Journal of Web Engineering, and program committee chair of the IADIS (International Association for Development of the Information Society) International Conference on WWW and the Internet. He is a collaborator with the Web Science Research Initiative (WSRI) speaking frequently on the evolving field of Web Science. He is a member of the International Academy of Digital Arts and Sciences (IADAS) and on the executive advisory board of ACM SigWeb.
	Prof. Philip S. Yu University of Illinois, USA
Title:
Mining Evolving Data Streams for Real-time Monitoring Applications
Abstract: The problem of streaming data has become increasingly importance in recent years. The ubiquitous presence of data streams in a number of practical domains has generated a lot of research in this area. Example applications include surveillance for terrorist attack, network monitoring for intrusion detection, and others. Problems such as data mining which have been widely studied for traditional data sets cannot be easily solved for the data stream domain. This is because the large volume of data arriving in a stream renders most algorithms to inefficient as most mining algorithms require multiple scans of data which is unrealistic for streaming data. More importantly, the characteristics of the data stream can change over time and the evolving pattern needs to be captured. In addition, we need to consider the problem of resource allocation in mining data streams. Due to the large volume and the high speed of streaming data, mining algorithms must cope with the effects of system overload. Furthermore, the stream data can often be noisy as in sensor data streams. Thus, how to achieve optimum results under the various constraints becomes a challenging task. In this talk, I¡¯ll provide an overview, discuss the issues and focus on how to mine uncertain data streams and perform resource adaptive computation. Resume: Philip S. Yu is a Professor in the Department of Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information and Technology. He spent most of his career at IBM Thomas J. Watson Research Center and was manager of the Software Tools and Techniques group. His research interests include data mining, Internet applications and technologies, database systems, multimedia systems, parallel and distributed processing, and performance modeling. Dr. Yu has published more than 560 papers in refereed journals and conferences. He holds or has applied for more than 300 US patents. Dr. Yu is a Fellow of the ACM and the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery from Data. He is on the steering committee of the IEEE Conference on Data Mining and was a member of the IEEE Data Engineering steering committee. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001-2004). He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he was the program chair or co-chairs of the 2009 IEEE Intl. Conf. on Service-Oriented Computing and Applications, the IEEE Workshop of Scalable Stream Processing Systems (SSPS¡¯07), the IEEE Workshop on Mining Evolving and Streaming Data (2006), the 2006 joint conferences of the 8th IEEE Conference on E-Commerce Technology (CEC' 06) and the 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE' 06), the 11th IEEE Intl. Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, the 2nd IEEE Intl. Workshop on Research Issues on Data Engineering: Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases, and the 2nd IEEE Intl. Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chair or co-chairs of the 2009 IEEE Intl. Conf. on Data Mining, the 2009 IEEE Intl. Conf. on Data Engineering, the 2006 ACM Conference on Information and Knowledge Management, the 1998 IEEE Intl. Conference on Data Engineering, and the 2nd IEEE Intl. Conference on Data Mining. He had received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 94th plateau of Invention Achievement Awards. He was an IBM Master Inventor. Dr. Yu received a Research Contributions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE Region 1 Award for "promoting and perpetuating numerous new electrical engineering concepts" in 1999. He received the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University.
	Prof. Kai Hwang University of Southern California, USA
Title:
Security and Privacy Issues in Cloud Computing and Their Solution Ideas
Abstract: Gartner Report has ranked virtualization and cloud computing as the top two technologies in 2009. In this talk, Dr. Hwang will assess the role of virtualization technology in protecting cloud resources and datasets used in three Cloud service models, namely the SaaS, PaaS, and IaaS. He presents virtualization techniques to secure clouds and a hierarchical reputation system for data protection in distributed datacenters. Virtual machines enable dynamic cloud resource provisioning and secure the datacenters in web-scale cloud applications. In particular, security and privacy protection in geospatial query processing will be assessed in cloud-enabled environment. This talk is based on joint research work performed at USC Internet and Cloud Computing Lab in collaboration with the next-generation Internet research group at the Institute of Computing Technology, Chinese Academy of Sciences. Resume: Dr. Kai Hwang is a Professor of Electrical Engineering and Computer Science at the Univ. of Southern California (USC). He received the Ph.D. in Electrical Engineering and Computer Science from the Univ. of California, Berkeley. He has published 8 books and over 210 scientific papers in computer architecture, parallel and distributed computing, network security, and Internet applications. He was awarded an IEEE Fellow in 1986 for making significant contributions in computer architecture, digital arithmetic, and parallel processing. He received the 2004 Outstanding Achievement Award from China Computer Federation. Hwang is the founding Editor of the Journal of Parallel and Distributed Computing. He has produced 21 Ph.D. students at USC and Purdue. Several of his former students are elevated to IEEE Fellows or IBM Fellows. His latest research publications cover e-commerce, cloud computing, P2P networks, reputation systems, Grid performance, and copyright protection. He has delivered 30 keynote addresses in major IEEE/ACM Conferences and performed advisory and consulting work for IBM, Intel, MIT Lincoln Lab., Academia Sinica, ETL in Japan, and INRIA in France. Contact him at kaihwang@usc.edu.
	Prof. Clark Thomborson The University of Auckland, New Zealand
Title:
Limited Autonomy
Abstract: We have performed a security analysis on a general class of autonomous systems. This analysis reveals some of the strengths and weaknesses of three organisational types. One type of organisation is strongest at fault tolerance, but is weakest at responding to changes in the system's environment or in the strategic goals of its owner. Another type of system organisation is very adaptable, but is not very fault-tolerant. A third type of organisation is fundamentally unanalysable, and is therefore unpredictable in at least some of its behaviours. However this third type, if well-designed and well-implemented, can be both fault-tolerant and adaptable within its predictable range and domain. We see no realistic prospect of anyone ever designing a completely autonomous system, except within a simulation. Resume: Professor Clark Thomborson joined the Computer Science department at the University of Auckland in 1996. He has published more than one hundred refereed papers in computer systems security, performance, and algorithms. His current research focus is on requirements and architectures for secure computer systems in the context of their economic, legal, and socially-mediated functions and controls. Clark's prior academic positions were at the University of Minnesota, and at the University of California at Berkeley, with consultancies or temporary positions at MIT, Microsoft Research (Redmond), InterTrust, IBM Yorktown, IBM Almaden, Institute for Technical Cybernetics (Slovakia), and Xerox PARC. He has commercial experience in the USA as a systems integrator, at Digital Biometrics, LaserMaster, and Nicolet Instrument Corporation. Under his birth name Clark Thompson, he was awarded a PhD in Computer Science from Carnegie-Mellon University and a BS (Honors) in Chemistry from Stanford.