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Keynote Speakers    

Dr. Ruay-Shiung Chang


Prof. Peter M.A. Sloot


Dr. Stephen S. Yau


Prof. Jack Dongarra

Dr. Timothy K. Shih
Dr. Carlos Ramos
Prof. Xiaohua Hu Dr. Irwin King Prof. Kyu-Young Whang


Ruay-Shiung Chang,
Department of Computer Science and Information Engineering,
National Dong Hwa University


Computer Science: Where Is the Next Frontier?

The first all-electronic computer ENIAC was built in 1945 at the University of Pennsylvania. After nearly 65 years, computer has permeated into every facet of our lives. During these 65 years, many breakthroughs in hardware and software technology bring computers to this status quo. However, where do we go from here? Can computers and computer industries serve again as the locomotive to save and drive the world civilization and economy into the future? In this talk, we will suggest and introduce some promising fields that could have a big impact on the research and development of computers in particular and on the mankind in general. Some of the ideas may be deemed crazy. But who knows? You will be the judge.

About Dr. Ruay-Shiung Chang
Ruay-Shiung Chang received his B.S.E.E. degree from National Taiwan University in 1980 and his Ph.D. degree in Computer Science from National Tsing Hua University in 1988. He is now a professor in the Department of Computer Science and Information Engineering, National Dong Hwa University. His research interests include Internet, wireless networks, RFID and grid computing. He has published more than 70 peer-reviewed journal papers and numerous international conference papers. He is an editor for International Journal of Internet Protocol Technology, Journal of Internet Technology, and Journal of Convergence Information Technology. Dr. Chang is a member of ACM, a senior member of IEEE, and a founding member of Taiwan Institute of Information and Computing Machinery. Dr. Chang also served on the advisory council for the Public Interest Registry (www.pir.org) from 2004/5 to 2007/4.
  


Prof. Peter M.A. Sloot,
Full Professor of Computational Sciences and Scientific Director of the Informatics Institute
University of Amsterdam
Understanding and Fighting HIV/AIDS with Computational Science
Simulating the evolution of the Human Immunodeficiency Virus (HIV) epidemic requires a detailed description of the population network, especially for small populations in which individuals and their 'temporal spatial' contacts can be represented in detail and with high accuracy. We introduce the concept of a Complex Agent Network(CAN) to model the HIV epidemics by combining agent-based modelling and complex networks, in which agents represent individuals that have sexual interactions. The applicability of CANs is demonstrated by constructing and executing a detailed HIV epidemic model for homosexual man in Amsterdam, including a distinction between steady and casual relationships. We focus on homosexual contacts because they play an important role in HIV epidemics and have been tracked in Amsterdam for a long time. Our experiments show good correspondence between the historical data of the Amsterdam cohort and the simulation results. In this lecture Peter Sloot will present ongoing work on modeling infectious diseases from the molecule all the way up to the population. Dr. Sloot will also identify the major hurdle for such research and a possible way to overcome that hurdle.
 About Prof. Peter M.A. Sloot
Prof. Peter M.A. Sloot studied chemistry and physics, finished his Computational BioPhysics PhD work at the Dutch Cancer institute (NKI) in 1988 with Prof. Carl Figdor and did various postdocs abroad. In 1996 he received the prestigious chair in Computational Physics from the Dutch Physics Society and is since 2001 he is a full professor in Computational Sciences at the Faculty of Science of the Universiteit van Amsterdam, the Netherlands. In his research, he focuses on the theory and application of complex systems through distributed mesoscopic computer simulation; trying to understand how information progresses through various spatial and temporal scales. He is strongly interested in applying his idea’s to BioMedical systems. Internationally he is a strong advocate of the field of Computational Science: he has been the General Chair of the ICCS series of conferences on Computational Sciences since 2002 and director of the related MSc program. Up to 2007 he has co-edited with Prof. Jack Dongarra over 20,000 peer reviewed pages of research from this conference series in Springer’s LNCS. He is an external advisor to the UK eScience Strategic Advisory Team and Editor in Chief of the Elsevier’s science journal: Future Generation of Computing Systems as well as Associate editor of The International Transactions on Systems Science and Applications.

The average number of keynotes and invited lectures over the past 5 years were 8 per year; this in addition to public lectures and interviews. Over the past decade he acquired funding for 9 NWO (NSF) and KNAW (Academy of Science) projects and 8 large EU projects. Currently he leads the EU ViroLab project (www.virolab.org) and participates in 4 more EU projects, 5 NWO projects and 1 NIH project. In 1996 he received a 5 year NNV extraordinary professorship in numerical physics.

Peter Sloot has over 320 peer reviewed publications, among which ~ 70as the 1st author, 77 ISI registered peer-reviewed journal papers, 180proceeding papers and 10 chapters in books.He owns the IPR of 2 Patents and Trademarks and supervise(d) 18PhD theses.

  
Dr. Stephen S. Yau,
Director, Information Assurance Center
Professor of Computer Science and Engineering
Arizona State University
Tempe, Arizona, USA
Adaptive QoS and Resource Management for Service-based Software Systems

The rapid adoption of service-oriented architecture in many large-scale distributed applications, such as scientific computing, e-business and healthcare, is due to the characteristics of service-based software systems (SBS), including loosely-coupling, late-binding, composability, and adaptability. These characteristics allow rapid composition of SBS from services provided by various organizations, and adaptation of SBS to satisfy multiple QoS or new functional requirements. To do so, the SBS needs to be aware of the current service QoS and resource status, estimate possible future changes of service QoS and resource status, and adapt service configurations and allocate resources accordingly. How to estimate the QoS of an SBS based on the QoS of individual services composing the SBS, and properly allocate computing and communication resources to improve service QoS are not well-understood. Hence, new techniques for adaptive QoS and resource management for SBS are needed.

In this talk, the challenges for developing SBS to satisfy multiple QoS in dynamic operating environments and current techniques useful for the development, such as QoS-aware service composition, distributed resource management, autonomic computing, and software cybernetics, will be discussed. Important issues, such as establishing QoS models for SBS, optimal resource allocation for workflows in SBS, and development support for generating autonomic monitoring and adaptation capabilities, and the ideas to address these issues will be presented.

About Dr. Stephen S. Yau   
Stephen S, Yau is currently the director of Information Assurance Center and a professor of computer science and engineering at Arizona State University (ASU), Tempe, Arizona, USA. He served as the chair of the Department of Computer Science and Engineering at ASU in 1994-2001. Previously, he was on the faculties of Northwestern University, Evanston, Illinois, and University of Florida, Gainesville.

He served as the president of the Computer Society of the Institute of Electrical and Electronics Engineers (IEEE) and American Federation of Information-Processing Societies (AFIPS). He was on the IEEE Board of Directors, and the Board of Directors of Computing Research Association. He served as the editor-in-chief of IEEE COMPUTER magazine, and organized many national and international major conferences, including the 1974 National Computer Conference sponsored by AFIPS, Association of Computing Machinery, IEEE Computer Society, and Society for Computer Simulation, and the 1989 World Computer Congress sponsored by International Federation for Information Processing (IFIP). He founded the Annual International Computer Software and Applications Conference (COMPSAC) sponsored by the IEEE Computer Society, in 1977.

His current research includes service-based systems, trustworthy computing, software engineering, mobile ad hoc networks and ubiquitous computing. He has received many awards and recognition for his accomplishments, including the Tsutomu Kanai Award and Richard E. Merwin Award of the IEEE Computer Society, the IEEE Centennial Awards and Third Millennium Medal, the Outstanding Contributions Award of the Chinese Computer Federation, and the Louis E. Levy Medal of the Franklin Institute. He is a Life Fellow of the IEEE and a Fellow of the American Association for the Advancement of Science.


  
  
Prof. Jack Dongarra,
Innovative Computing Laboratory,
EECS Department, University of Tennessee
Five Important Concepts to Consider when Using Computing High Performance Systems at Scale 

In this talk we examine how high performance computing has changed over the last 10-year and look toward the future in terms of trends. These changes have had and will continue to have a major impact on our software. Some of the software and algorithm challenges have already been encountered, such as management of communication and memory hierarchies through a combination of compile--time and run--time techniques, but the increased scale of computation, depth of memory hierarchies, range of latencies, and increased run--time environment variability will make these problems much harder.

We will look at five areas of research that will have an importance impact in the development of software.

We will focus on following themes:

  • Redesign of software to fit multicore architectures
  • Automatically tuned application software
  • Exploiting mixed precision for performance
  • The importance of fault tolerance
  • Communication avoiding algorithms
About Prof. Jack Dongarra  
Jack Dongarra received a Bachelor of Science in Mathematics from Chicago State University in 1972 and a Master of Science in Computer Science from the Illinois Institute of Technology in 1973. He received his Ph.D. in Applied Mathematics from the University of New Mexico in 1980. He worked at the Argonne National Laboratory until 1989, becoming a senior scientist. He now holds an appointment as University Distinguished Professor of Computer Science in the Computer Science Department at the University of Tennessee and holds the title of Distinguished Research Staff in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), Turing Fellow at Manchester University, and an Adjunct Professor in the Computer Science Department at Rice University. He is the director of the Innovative Computing Laboratory at the University of Tennessee. He is also the director of the Center for Information Technology Research at the University of Tennessee which coordinates and facilitates IT research efforts at the University.

He specializes in numerical algorithms in linear algebra, parallel computing, the use of advanced-computer architectures, programming methodology, and tools for parallel computers. His research includes the development, testing and documentation of high quality mathematical software. He has contributed to the design and implementation of the following open source software packages and systems: EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. He has published approximately 200 articles, papers, reports and technical memoranda and he is coauthor of several books. He was awarded the IEEE Sid Fernbach Award in 2004 for his contributions in the application of high performance computers using innovative approaches and in 2008 he was the recipient of the first IEEE Medal of Excellence in Scalable Computing. He is a Fellow of the AAAS, ACM, IEEE, and SIAM and a member of the National Academy of Engineering.


  

  
Dr. Timothy K. Shih,
Dean, College of Computer Science,
Asia University, Taiwan

Video Forgery  

Video Forgery is a technique for generating fake video by altering, combining, or creating new video contents. We change the behavior of actors in a video. For instance, the outcome of a 100-meter race in the Olympic Game can be falsified. We track objects and segment motions using a modified mean shift mechanism. The resulting video layers can be played in different speeds and at different reference points with respect to the original video. In order to obtain a smooth movement of target objects, a motion interpolation mechanism is proposed based on reference stick figures (i.e., a structure of human skeleton) and video inpainting mechanism. The video inpainting mechanism is performed in a quasi-3D space via guided 3D patch matching. Interpolated target objects and background layers are fused. It is hard to tell whether a falsified video is the original. We demonstrate the original and the falsified videos in our website at http://member.mine.tku.edu.tw/www/TIP2008/ and http://member.mine.tku.edu.tw/www/ACMMM08VideoDemo. Video falsifying may create a moral problem. Our intension is to create special effects in movie industry.

About Dr. Timothy K. Shih   
Dr. Shih is a Professor and the Dean of College of Computer Science, Asia University, Taiwan. He is a Fellow of the Institution of Engineering and Technology (IET). In addition, he is a senior member of ACM and a senior member of IEEE. Dr. Shih also joined the Educational Activities Board of the Computer Society. His current research interests include Multimedia Computing and Distance Learning. Dr. Shih has edited many books and published over 430 papers and book chapters, as well as participated in many international academic activities, including the organization of more than 60 international conferences. He was the founder and co-editor-in-chief of the International Journal of Distance Education Technologies, published by Idea Group Publishing, USA. Dr. Shih is an associate editor of the ACM Transactions on Internet Technology and an associate editor of the IEEE Transactions on Learning Technologies. He was also an associate editor of the IEEE Transactions on Multimedia. Dr. Shih has received many research awards, including research awards from National Science Council of Taiwan, IIAS research award from Germany, HSSS award from Greece, Brandon Hall award from USA, and several best paper awards from international conferences. Dr. Shih has been invited to give more than 30 keynote speeches and plenary talks in international conferences, as well as tutorials in IEEE ICME 2001 and 2006, and ACM Multimedia 2002 and 2007.

  

Dr. Carlos Ramos,
Director of GECAD (the Knowledge Engineering and Decision Support Research Centre)
and Coordinator professor at the ISEP

Ambient intelligence the next step for artificial intelligence  

Ambient intelligence (AmI) deals with a new world of ubiquitous computing devices, where physical environments interact intelligently and unobtrusively with people. These environments should be aware of people's needs, customizing requirements and forecasting behaviors. AmI environments can be diverse, such as homes, offices, meeting rooms, schools, hospitals, control centers, vehicles, tourist attractions, stores, sports facilities, and music devices. Artificial intelligence research aims to include more intelligence in AmI environments, allowing better support for humans and access to the essential knowledge for making better decisions when interacting with these environments. In this talk I will present the challenging concept of Ambient Intelligence, seen from a point of view of Artificial Intelligence.

  About Dr. Carlos Ramos
Carlos Ramos got his graduation from the University of Porto, Portugal, in 1986 and the PhD degree from the same university in 1993. He is Coordinator Professor of the Department of Informatics at the Institute of Engineering – Polytechnic of Porto (ISEP-IPP). His main interests are Artificial Intelligence and Decision Support Systems, recently with more emphasis on Ambient Intelligence. He is Director of GECAD (Knowledge Engineering and Decision Support Research Centre), the largest R&D centre of the Polytechnic system in Portugal, and dedicated to AI topics. He coordinates the Ambient Intelligence and Decision Support group of GECAD. Carlos Ramos has about 50 publications in scientific journals and magazines and more than 200 publications in Scientific Conferences.

  

Prof. Xiaohua (Tony) Hu,
Associate Professor,
College of Information Science & Technology
Drexel University, Philadelphia PA 19104, USA

Data Mining and its Application in Bioinformatics  

In this talk, we will discuss some data mining methods and their applications in bioinformatics domain, focusing on integrating text mining and predictive modeling to analyze biomolecular network. Our method consists of three phases. In phase 1, we discuss a semi-supervised efficient learning approach to automatically extract biological relationships such as protein-protein interaction, protein-gene interaction from the biomedical literature databases to construct the biomolecular network. In Phase 2, a novel scale-free network clustering approach is applied to the biomolecular network to obtain various sub-networks. In Phase 3, a computational model is generated for the sub-network and simulated to predict their behavior in the cellular context. We discuss and evaluate some of the advanced computational models, in particular, state-space model, probabilistic Boolean Network model, fuzzy logic model. The modeling results represent hypotheses that are tested against high-throughput datasets (microarrays and/or genetic screens) for both the natural system and perturbations. Experimental results on time-series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large biomolecular network.

    About Prof. Xiaohua (Tony) Hu
Xiaohua (Tony) Hu is currently an associate professor and the founding director of the data mining and bioinformatics lab at the College of Information Science and Technology, Drexel University, USA, one of the best information science schools in USA (ranked as #1 in 1999 and #3 in 2009 in information systems by U.S. News & World Report). He is the now also serving as the IEEE Computer Society Bioinformatics and Biomedicine Steering Committee Chair, and the IEEE Computer Society Granular Computing Steering Committee Co-Chair.

Tony is a scientist, teacher and entrepreneur. He joined Drexel University in 2002, founded the International Journal of Data Mining and Bioinformatics (SCI indexed) in 2006, International Journal of Granular Computing, Rough Sets and Intelligent Systems in 2008. Earlier, he worked as a research scientist in the world-leading R&D centers such as Nortel Research Center, GTE labs and HP Labs. In 2001, he founded the DMW Software in Silicon Valley, California. His research ideas have been integrated into many commercial products and applications. Tony’s current research interests are in biomedical literature data mining, bioinformatics, text mining, semantic web mining and reasoning, rough set theory and application, information extraction and information retrieval. He has published more than 160 peer-reviewed research papers in various journals, conferences and books such as various IEEE/ACM Transactions. co-edited 14 books/proceedings. He has received a few prestigious awards including the 2005 National Science Foundation (NSF) Career award, the best paper award at the 2007 International Conference on Artificial Intelligence, the best paper award at the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, the 2007 IEEE Bioinformatics and Bioengineering Outstanding Contribution Award, the 2006 IEEE Granular Computing Outstanding Service Award, and the 2001 IEEE Data Mining Outstanding Service Award. His research projects are funded by the National Science Foundation (NSF), US Dept. of Education, and the PA Dept. of Health and he has obtained more than US$4.0 millions research grants in the past 4 years as PI or Co-PI.


  

Dr. Irwin King,
Department of Computer Science and Engineering
The Chinese University of Hong Kong

The Era of Social Computing  

The Web has changed the landscape of how humans interact socially. With the advent of Web 2.0, Social Computing has emerged as a new and innovative paradigm that changes the way we communicate, interact, and learn. Social Computing involves the investigation of collective intelligence by using computational techniques such as machine learning, data mining, natural language processing, etc. on social behavioral data collected from blogs, wikis, emails, instant messages, clickthrough data, query logs, social bookmarks, tags, etc. In this talk, I will first introduce Social Computing by outlining some of the unique characteristics and aspects that are found on the various social platforms. Applications in each of the platforms will be presented to further demonstrate the use of these new technologies to enhance and enrich our lives. Lastly, I will conclude with some current challenges and potential future promises of Social Computing.

    About Dr. Irwin King
Dr. King's research interests include machine learning, web intelligence & social computing, and multimedia processing. In these research areas, he has over 160 technical publications in journals (JMLR, ACM TOIS, IEEE TNN, Neurocomputing, NN, IEEE BME, PR, IEEE SMC, JAMC, JASIST, IJPRAI, DSS, etc.) and conferences (NIPS, IJCAI, CIKM, SIGIR, KDD, PAKDD, ICDM, WWW, WI/IAT, WCCI, IJCNN, ICONIP, ICDAR, etc.). In addition, he has contributed over 20 book chapters and edited volumes. Moreover, Dr. King has over 30 research and applied grants. One notable system he has developed is the CUPIDE (Chinese University Plagiarism IDentification Engine) system, which detects similar sentences and performs readability analysis of text-based documents in both English and in Chinese to promote academic integrity and honesty.

Dr. King is an Associate Editor of the IEEE Transactions on Neural Networks (TNN) and IEEE Computational Intelligence Magazine (CIM). He is a member of the Editorial Board of the Open Information Systems Journal, Journal of Nonlinear Analysis and Applied Mathematics, and Neural Information Processing–Letters and Reviews Journal (NIP-LR). He has also served as Special Issue Guest Editor for Neurocomputing, International Journal of Intelligent Computing and Cybernetics (IJICC), Journal of Intelligent Information Systems (JIIS), and International Journal of Computational Intelligent Research (IJCIR). He is a senior member of IEEE and a member of ACM, International Neural Network Society (INNS), and Asian Pacific Neural Network Assembly (APNNA). Currently, he is serving the Neural Network Technical Committee (NNTC) and the Data Mining Technical Committee under the IEEE Computational Intelligence Society (formerly the IEEE Neural Network Society). He is also a Vice-President and Governing Board Member of the Asian Pacific Neural Network Assembly (APNNA).

Dr. King joined the Chinese University of Hong Kong in 1993. He received his B.Sc. degree in Engineering and Applied Science from California Institute of Technology, Pasadena and his M.Sc. and Ph.D. degree in Computer Science from the University of Southern California, Los Angeles.


  

Prof. Kyu-Young Whang,
Distinguished Professor, KAIST, Korea

The Ubiquitous DBMS

Recent widespread use of mobile technologies and advancement in computing power prompted strong needs of database systems that can be used in small devices such as sensors, cellular phones, PDA, ultra PCs, and navigators. We call database systems that are customizable from small-scale applications for small devices to large-scale applications such as large-scale search engines ubiquitous database management systems (UDBMSs). In this talk, we first review requirements of UDBMSs. The requirements we identified include selective convergence (or “devicetization”), flash-optimized storage system, data synchronization, supportability of unstructured/semi-structured data, and complex database operations. We then review existing systems and research prototypes. We first review the functionality of UDBMSs including the footprint size, support of standard SQL, supported data types, transactions, concurrency control, indexing, and recovery. We then review the supportability of requirements by those UDBMSs surveyed. We highlight ubiquitous features of a family of Odysseus systems that have been under development at KAIST for over 19 years. Functionalities of Odysseus can be “devicetized” or customized depending on the device types and applications as in Odysseus/Mobile for small devices, Odysseus/XML for unstructured/semistructured data, Odysseus/GIS for map data, and Odysseus/IR for large-scale search engines. We finally present research topics that are related to the UDBMSs.

    About Prof. Kyu-Young Whang
Kyu-Young Whang is a KAIST Distinguished Professor, Professor of Computer Science, and Director of Advanced Information Technology Research Center (AITrc) at KAIST. Previously, he was with IBM T.J.Watson Research Center from 1983 to 1990. Since joining KAIST in 1990, he has been leading the Odysseus DBMS/Search Engine project featuring tight-coupling of DBMS with information retrieval (IR) and spatial functions. Dr. Whang is one of the pioneers of probabilistic counting, which nowadays is being widely used in approximate query answering, sampling, and data streaming. One of the algorithms he co-developed at IBM Almaden (then San Jose) Research Lab in 1981 has been made part of DB2. Dr. Whang is the author of the first main-memory relational query optimization model developed in 1985 and reported in 1990 in ACM TODS in the context of Office-by-Example (OBE). This model influenced subsequent optimization models of commercial main-memory DBMSs. His research has covered a wide range of database issues including physical database design, query optimization, DBMS engine technologies, and more recently, IR, spatial databases, data mining, and XML. Dr. Whang is the Coordinating Editor-in-Chief of the prestigious VLDB Journal, having served the journal for 19 years from its inception as its founding editorial board member. He is a Trustee Emeritus of the VLDB Endowment and served the international academic community as the General Chair of VLDB2006, DASFAA2004, and PAKDD2003, as a PC Co-Chair of VLDB2000, CoopIS1998, and ICDE2006, and as an editorial board member of journals such as IEEE TKDE, The WWW Journal, and IEEE Data Engineering Bulletin. He served as the Chair of the Steering Committee of the DASFAA International Conference and as a founder of the Korea-Japan Database Workshop (KJDB) annually held alternately in Korea and Japan. He is a member of the ACM SIGMOD Dissertation Award Committee and served as a member of many 10-year Best or Influential Paper Award committees of VLDB and IEEE ICDE. He served as an IEEE Distinguished Visitor from 1989 to 1990 and was invited to ACM SIGMOD Distinguished Profile in Databases in 2007. He earned his Ph.D. from Stanford University in 1984. Dr. Whang is an IEEE Fellow, a member of the ACM and IFIP WG 2.6.
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