Prof. Richard M. Karp
(1985 Turing Award Recipient)
University of California at Berkeley, USA

Abstract

This talk will trace the growing influence of fundamental ideas from computer science on the nature of research in a number of scientific fields. There is a growing awarenessthat information processing lies at the heart of the processes studied in fields as diverse as quantum mechanics, statistical physics, nanotechnology, neuroscience, linguistics, economics and sociology. Increasingly, mathematical models in these fields are expressed in algorithmic languages and describe algorithmic processes. The speaker will briefly describe connections between quantum computing and the foundations of quantum mechanics, and between statistical mechanics and phase transitions in computation. He will indicate how the growth of the Web has created new phenomena to be investigated by sociologists and economists. He will then focus in greater detail on computational molecular biology, where the view of living cells as complex information processing systems has become the dominant paradigm, and will discuss specific algorithmic problems arising in the sequencing of genomes, the comparative analysis of the resulting genomic sequences,the modeling of networks of interacting proteins, and the associations between genetic variation and disease.

Bio

Richard M. Karp was born in Boston, Massachusetts on January 3, 1935. He attended Boston Latin School and Harvard University, receiving the Ph.D. in 1959. From 1959 to 1968 he was a member of the Mathematical Sciences Department at IBM Research. From 1968 to 1994 and from 1999 to the present he has been a Professor at the University of California, Berkeley, where he held the Class of 1939 Chair and is currently a University Professor. From 1988 to 1995 and 1999 to the present he has been a Research Scientist at the International Computer Science Institute in Berkeley. From 1995 to 1999 he was a Professor at the University of Washington. During the 1985-86 academic year he was the co-organizer of a Computational Complexity Year at the Mathematical sciences research Institute in Berkeley. During the 1999-2000 academic year he was the Hewlett-Packard Visiting Professor at the Mathematical Sciences Research Institute. The unifying theme in Karp's work has been the study of combinatorial algorithms. His 1972 paper, "Reducibility Among Combinatorial Problems," showed that many of the most commonly studied combinatorial problems are NP-complete, and hence likely to be intractable. Much of his work has concerned parallel algorithms, the probabilistic analysis of combinatorial optimization algorithms and the construction of randomized algorithms for combinatorial problems.

His current activities center around algorithmic methods in genomics and computer networking. He has supervised thirty-six Ph.D. dissertations. His honors and awards include: U.S. National Medal of Science, Turing Award, Fulkerson Prize, Harvey Prize (Technion), Centennial Medal (Harvard), Lanchester Prize, Von Neumann Theory Prize, Von Neumann Lectureship, Distinguished Teaching Award (Berkeley), Faculty Research Lecturer (Berkeley), Miller Research Professor (Berkeley), Babbage Prize and eight honorary degrees. He is a member of the U.S. National Academies of Sciences and Engineering, the American Philosophical Society and the French Academy of Sciences, and a Fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the Association for Computing Machinery and the Institute for Operations Research and Management Science.

Prof. Dieter Fensel
Director DERI Innsbruck
University of Innsbruck

Abstract

Computer science is entering a new generation. The previous generation was based on abstracting from hardware. The emerging generation comes from abstracting from software and sees all resources as services in a service-oriented architecture (SOA). In a world of services, it is the service that counts for a customer and not the software or hardware components that implement the service. Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to in-house solution of companies. A service web will have billions of services. While service orientation is widely acknowledged for its potential to revolutionize the world of computing by abstracting form underlying hardware and software layers, that success depends on resolving fundamental challenges that SOA does not address currently. The mission of Service Web 3.0 is to provide solutions to integration and search that will enable the Service Oriented Architecture (SOA) revolution on a worldwide scale. Hereby we must focus on three major areas where we need to extend current approaches towards service orientation:

• Web technology as an infrastructure and underlying infrastructure for integration of services at a world wide scale.
• Semantic Web technology as a means to abstract from syntax to semantics; and
• Web 2.0 as a means to structure human-machine cooperation in an efficient and costeffective manner

Service Web 3.0 will place computing and programming at the services layer providing the real goal of computing: problem solving in the hands of end users through a properly balanced cooperation approach. 2 Humans are much better in solving certain tasks (capture recognition, image descriptions, common sense reasoning, f.e., http://video.google.com/videoplay?docid=-8246463980976635143&hl=en).

Bio Sketch

Univ.-Prof. Dr. Dieter Fensel is the scientific director of the Digital Enterprise Research Institute (DERI) at the University Innsbruck, Austria, and one of the leading experts in the fields of Semantic Web, Semantic Web Services, and Semantically Enabled Service-Oriented Architectures. He graduated in Social Science (Free University of Berlin) and Computer Science (Technical University of Berlin) in 1989. He obtained his PhD in Economic Science from the University of Karlsruhe in 1993. Prof. Dr. Dieter Fensel received his Habilitation in Applied Computer Science in 1998. He has published over 200 papers via scientific books and journals, conferences, and workshop contributions, co-organized over 200 academic workshops and conferences, and had a major contribution to the establishment of the most important scientific conferences, organizational instruments and publication channels in the field. Contact him at dieter.fensel@deri.at. More information is available at www.fensel.com.

Toyoaki Nishida
Dept. of Intelligence Science and Technology.
Graduate School of Informatics
Kyoto University, Japan

Abstract

Conversation is the most natural communication means for people to communicate with each other. I believe that conversation plays a critical role in realizing a paradigm of human-centered web intelligence in which web intelligence engines are grounded on the human society. We are currently building a computational framework for circulating information in a conversational fashion, using information packages called conversation quanta that encapsulate conversational scenes. Technologies are being developed for acquiring conversation quanta on the spot, accumulating them in a visually recognizable form, and reusing them in a situated fashion. Conversational Informatics constitutes the theoretical foundation for measurement, analysis, and modeling of conversation. I will overview recent results in Conversational Informatics that will help achieve our vision. I will also discuss our approach in the context of Social Intelligence Design aimed at the understanding and augmentation of social intelligence for collective problem solving and learning.

Bio Sketch

Toyoaki Nishida is a professor of Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University. He received the Doctor of Engineering degree from Kyoto University in 1984. His research centers on artificial intelligence and human computer interaction. In 2001, he founded a series of international workshops on social intelligence design (see http://www.ii.ist.i.kyoto-u.ac.jp/sid/ for more details). Then, he broadened the scope of research to include understanding and augmenting conversational communication, and opened up a new field of research called Conversational Informatics. Currently, he leads several projects on social intelligence design and conversational informatics. He is a member of the board of directors of IPS (Information Processing Society) of Japan and JSAI (Japanese Society for Artificial Intelligence). He serves as an editorial board member of several academic journals, including Web Intelligence and Agent Systems, AI & Society, and Journal of JSAI (editor-in-chief).

Prof. Yoav Shoham
Professor of Computer Science, Stanford University, USA

Abstract

At this point, restricted to rather specialized areas, and even there must be taken with a grain of salt. But at the same time you can't afford not to know it; there is currently no better underpinning for understanding multiagent systems. I will elaborate using experience in both academia and industry.

Bio Sketch

Yoav Shoham is Professor of Computer Science at Stanford University, where he has been since receiving his PhD in Computer Science from Yale University in 1987 and spending an abbreviated post-doctoral position at the Weizmann Institute of Science. He has worked in various areas of AI, including temporal reasoning, nonmonotonic logics and theories of commonsense. Shoham's interest in recent years has been in multi-agent systems, including the interaction between computer science and game theory. His particular focus has been on auctions and mechanism design, and multiagent learning. Shoham is a fellow of the American Association of Artificial Intelligence, and charter member of the Game Theory Society. He is an author of four books and numerous articles. He is also a founder of several successful e-commerce software companies.

Dr. Eugene Santos Jr.
Thayer School of Engineering at Dartmouth, USA

Abstract

Accounting for social, cultural, and political factors must form the basis for understanding decision-making, actions, and reactions of individuals, thus driving their behaviors and intentions. Clearly, the individual is not wholly defined by just personal social, cultural, and political beliefs but also functions within a group of individuals. Within these groups (or organizations), they assimilate a potentially wide variety of different social factors, which may or may not differ from their own. Also, the group itself can vary in degrees of complexity, styles of interaction, and so forth, resulting in highly dynamic and emergent modes of behaviors. Even more difficult, this also includes taking into account the values, attitudes, and beliefs of the local population/environment that the individual/group is situated within. Without all these factors, we cannot expect to effectively understand, analyze, or predict the behaviors and intentions of others which grows ever more critical as our society continnues to globalize and especially in today's conflicts and catastrophes. Thus, the need for a comprehensive modeling framework is evident as our only real hope of addressing such complexity. However, to date, only small isolated groups of pertinent behavioral factors have been studied, while there is little or no work towards developing a general unified and comprehensive approach that is also computational. The major challenges we face can be summed up in the following questions:

1. For prediction and explanation of intent and behavior, how does one computationally model individual or organizations and their emergent interactions with others, in various situations?
2. How does one organize and build the necessary social, cultural, political, behavioral, etc. knowledge- base?
3. How do you avoid brittleness and overspecialization? How do you construct these models efficiently and effectively, and dynamically evolve such models over time based on changing cultural and social factors?
4. How do you validate your models?

In this talk, we will explore these challenges and focus on addressing pragmatic and computational issues in such modeling and examine some existing real-world efforts, current solutions, and open-questions.

Bio Sketch

Dr. Eugene Santos, Jr. is a Professor of Engineering in the Thayer School of Engineering at Dartmouth College. He received his B.S. ('85) in Mathematics and Computer Science from Youngstown State University, a M.S. ('86) in Mathematics from Youngstown State University, as well as Sc.M. ('88) and Ph.D. ('92) degrees in Computer Science from Brown University. His areas of research interest include artificial intelligence, intent inferencing, information retrieval, automated reasoning, decision science, adversarial reasoning, user modeling, natural language processing, probabilistic reasoning, knowledge engineering, verification and validation, protein folding, load balancing, virtual reality, and active user interfaces. He has served on many major conference program committees from intelligent agents to evolutionary computing. He is currently an associate editor for the IEEE Transactions on Systems, Man, and Cybernetics and for the International Journal of Image and Graphics, and is also on the editorial advisory board for System and Information Sciences Notes.

Yiyu Yao
International WIC Institute
Beijing University of Technology
University of Regina, Canada

Abstract

In this talk, we examine the basic principles,ideas, and strategies of granular computing, and look at the potential applications and implicationsof granular computing to the studies of Web Intelligence (WI) and Brain Informatics (BI). We argue that granular computing may provide the necessary theory for designing and implementing new types of web-based information processing systems and developing a conceptual model of the human brain.

Bio Sketch

Yiyu Yao is a Professor of Computer Science with the Department of Computer Science, University of Regina, Canada. He is an adjunct Professor of International WIC Institute at Beijing University of Technology, Xi’an Jiaotong University, and Chongqing University of Posts and Telecommunication.

Dr. Yao’s research interests include web intelligence, information retrieval, uncertain reasoning, non-classical logics, fuzzy sets, rough sets, interval computing, granular computing, data mining, intelligent agents, and applications of measurement theory, decision theory and information theory. Dr. Yao is actively involved in several research initiatives, including Web intelligence (2000-), rough sets (1990-), granular computing (1997-), information retrieval support systems (2001-), and research support systems (2003-).

Anant Jhingran
VP and CTO, IBM Silicon Valley Laboratory, USA

Abstract

There is a fundamental transformation that is taking place on the web around information composition through mashups. We first describe this transformation and then assert that this will also affect enterprise architectures. Currently the state-of-the-art in enterprises around information composition is federation and other integration technologies. These scale well, and are well worth the upfront investment for enterprise class, long-lived applications. However, there are many information composition tasks that are not currently well served by these architectures. The needs of Situational Applications (i.e. applications that come together for solving some immediate business problems) are one such set of tasks. Augmenting structured data with unstructured information is another such task. Our hypothesis is that a new class of integration technologies will emerge to serve these tasks, and we call it an enterprise information mashup fabric. In the talk, we discuss the information management primitives that are needed for this fabric, the various options that exist for implementation, and pose several, currently unanswered, research questions.

Bio Sketch

Dr. Anant Jhingran is a Distinguished Engineer, Vice President and the Chief Technology Officer for IBM's Information Management Division. Anant is responsible for the technical strategy of IBM's Information Management Software business, which has products and solutions in databases, content management, business intelligence, search and discovery, information integration and master data management. Previous to this job, Dr. Jhingran led the IBM team designing and building world-class solutions to meet the requirements of business analytics on structured and unstructured data. He has also been the director of Computer Science at the IBM Almaden Research Center where he managed the research scientists dedicated to advancing technology across foundations, software and services. Prior to joining Almaden Research, Dr. Jhingran was senior manager for e-Commerce and data management at IBM's T. J. Watson Research Center. He received his Ph.D. from UC at Berkeley in 1990. Anant has received several patents, outstanding innovation awards, and a corporate award for his contributions to DB2. He has authored over 20 academic papers, and is also a member of IBM Academy of Technology.

Eric Brill
Principal Researcher and head of the Text Mining, Search and Navigation Group at Microsoft Research

Abstract

While search engines are great tools, they are still ineffective at helping users with a vast array of information needs. In this talk, we will discuss some of the problems with search today, and research opportunities that will help us realize vastly more effective search engines in the future.

Bio Sketch

Eric Brill is a research director and head of the Text Mining, Search and Navigation Group at Microsoft Research, which primarily conducts research in the areas of Web search and advertising. Prior to joining Microsoft, he was a faculty member in the Department of Computer Science and Center for Language and Speech Processing at Johns Hopkins University. Academically, Eric has been active in the fields of information retrieval, natural language processing, machine learning, speech recognition and artificial intelligence.

Alon Halevy
Research Scientist, Google

Abstract

Data integration is a pervasive challenge faced in applications that need to query across multiple autonomous and heterogeneous data sources. Data integration is crucial in large enterprises, large-scale scientific projects, and government agencies. Data integration also holds the promise of fueling the next revolution of data content on the Web. This talk will review some the impressive progress on data integration made in research and in industry, but will argue that despite the progress, data integration is either still too hard for most users or does not address the real needs in applications. I will describe a new abstraction, dataspaces, that attempts to address these two challenges. I will give examples of data management at Web-scale at Google that motivate the need for dataspaces.

Bio Sketch

Alon Halevy is a member of technical staff at Google Inc. Before joining Google, Alon was a professor of Computer Science at the University of Washington, Seattle. Alon is the founder of two data integration companies, Nimble Technology and Transformic Inc. He is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and a 10-year Best Paper Award at the International Conference on Very Large Databases (VLDB 2006) for his work on data integration. In 2006, Alon was elected Fellow of the ACM.

Dr.Yong Shi
Research Center on Fictious Economy & Data Science
Chinese Academy of Sciences

Abstract

For last ten years, the researchers have extensively applied quadratic programming into classification, known as V. Vapnik's Support Vector Machine, as well as various applications. However, using optimization techniques to deal with data separation and data analysis goes back to more than thirty years ago. According to O. L. Mangasarian, his group has formulated linear programming as a large margin classifier in 1960's. In 1970's, A. Charnes and W.W. Cooper initiated Data Envelopment Analysis where a fractional programming is used to evaluate decision making units, which is economic representative data in a given training dataset. From 1980's to 1990's, F. Glover proposed a number of linear programming models to solve discriminant problems with a small sample size of data. Then, the speaker and his colleagues have extended such a research idea into classification via a number of methods in multiple criteria decision making: multiple criteria linear programming (MCLP) and multiple criteria quadratic programming (MQLP). This approach differs from statistics, decision tree induction, and neural networks. This talk intends to promote the research interests in the connection of optimization and data mining as well as real-life applications among the growing data mining communities.

Bio Sketch

Professor Yong Shi serves as the Executive Deputy Director, Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science and Associate Dean, School of Management, Graduate University of the Chinese Academy of Sciences. He has been the Charles W. and Margaret H. Durham Distinguished Professor of Information Technology, College of Information Science and Technology, Peter Kiewit Institute, University of Nebraska, USA since1999. Dr. Shi's research interests include business intelligence, data mining, multiple criteria decision making, information overload, and telecommunication management. He has published ten books, more than 100 papers in various journals and numerous conferences/proceedings papers. He is the Editor-in-Chief of International Journal of Information Technology and Decision Making (SCIE), an Area Editor of International Journal of Operations and Quantitative Management, a member of Editorial Board for a number of academic journals, including International Journal of Data Mining and Business Intelligence. Dr. Shi has received many distinguished awards including Outstanding Young Scientist Award, National Natural Science Foundation of China, 2001; Member of Overseas Assessor for the Chinese Academy of Sciences, May 2000; and Speaker of Distinguished Visitors Program (DVP) for 1997-2000, IEEE Computer Society. He has consulted or worked on business projects for a number of international companies in data mining and knowledge management.

Neel Sundaresan
Director, eBay Research Labs

Abstract

This talk will discuss the challenges and approaches to findability in an online marketplace. The focus is beyond search and relevance. In a marketplace that affords social commerce, findability is critical and serendipity affords stickiness. We will discuss these topics and more.

Bio Sketch

Neel Sundaresan is a Senior Director and Head of eBay Research Labs. His current research interests include Social Networks, Community Computing, Search and Classification, and Trust and Reputation. Prior to joining eBay , he was a founder and CTO of a startup focused on multi-attribute fuzzy search and network CRM. Prior to this, he was headed the eMerging Internet Technologies group at the IBM Research Center. There he built the first XML-based Search Engine. He was one of the early leaders in building XML technologies including schema-aware compression algorithms, application component generators and pattern-match systems and compilers. He built the first RDF reference implementation as a W3C standard recommendation. He led research work in other areas like domain specific search engines, multi-modal interfaces and assistive technologies, semantic transcoding, and web mining. Prior to this he worked on C++ compiler and runtime systems for massively parallel machines and for shared memory systems and also on retargetable compilers, program translators and generators. He has over 40 research publications and several patents to his credit. He has been a frequent speaker at several national and international technology conferences. He has advised several masters and PhD students. He has a masters degree in Mathematics and in Computer Science from IIT Mumbai and a PhD in Computer Science from Indiana University, Bloomington.

Andrew Tomkins
Yahoo VP for Search Research

Abstract

Non-professional creation of public online content has outstripped professional content creation of all forms, both online and offline. However, two orders of magnitude more content are created daily to flow through social networks, with as much as two more orders of magnitude still to come as user engagement increases. At the same time, content is diversifying in creation, consumption, and nature. In this talk, I'll cover these trends and their implications. I'll present some research results regarding online communities and semantic structures, and will close with some challenges for the future.

Bio Sketch

Andrew Tomkins is Chief Scientist of Search at Yahoo!, where his research interests include web search, web analysis, and online communities. Prior to joining Yahoo!, Andrew spent 8 years at IBM's Almaden Research Center, where he managed the information management principles group and served as Chief Scientist of the WebFountain project. He has published over eighty technical papers, and serves on the editorial boards of IEEE Internet Computing and ACM Transactions on the Web. Andrew received his PhD in Computer Science from Carnegie Mellon University in 1997.