Conference keynote speakers

A plenary talk will be given by a leader in the field of Behavioral, Economic and Socio-Cultural Computing research. The names of keynote speakers will be added as invitations are accepted.

Jian Pei
Title: User Behaviors in Social Networks and Big Data: Similarity and Egocentricity
In the era of Big Data, we want to understand both the similarity and differences about user behaviors. It is challenging due to, for example, the volume and high dimensionality of user behavior data. In this talk, I will showcase some recent exciting breakthroughs in my group. We develop a unified parametric model and a spectrum of similarity measures that present a series of tradeoffs between computational cost and strictness of matching between user neighborhoods in a social network setting. We also demonstrate how to conduct user egocentric analysis on high dimensional data.
Jian Pei is currently Professor of Computing Science at the School of Computing Science at Simon Fraser University, Canada. He is also an associate member of the Department of Statistics and Actuarial Science. His research interests can be summarized as developing effective and efficient data analysis techniques for novel data intensive applications. Particularly, he is currently interested in various techniques of data mining, Web search, information retrieval, data warehousing, online analytical processing, and database systems, as well as their applications in social networks, healthcare-informatics, business intelligence. Since 2000, he has published one monograph and over 200 research papers in refereed journals and conferences, has served in the organization committees and the program committees of over 200 international conferences and workshops, and has been a reviewer for the leading academic journals in his fields. He is the Editor-in-Chief of IEEE Transactions of Knowledge and Data Engineering (TKDE), and an associate editor or editorial board member of ACM Transactions on Knowledge Discovery from Data (TKDD), Data Mining and Knowledge Discovery, Statistical Analysis and Data Mining, Intelligent Data Analysis, and Journal of Computer Science and Technology. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a senior member of the Association for Computing Machinery (ACM).
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Xindong Wu
Title: Personalized Web News Filtering and Summarization
Information on the World Wide Web is congested with large amounts of news contents. Recommending, filtering, and summarization of Web news have become hot topics of research in Web intelligence, aiming to find interesting news for users and give concise content for reading. This talk presents our research on developing the Personalized News Filtering and Summarization system (PNFS). An embedded learning component of PNFS induces a user interest model and recommends personalized news. Two Web news recommendation methods are proposed to keep tracking news and find topic interesting news for users. A keyword knowledge base is maintained and provides real-time updates to reflect the news topic information and the users interest preferences. The non-news content irrelevant to the news Web page is filtered out. A keyword extraction method based on lexical chains is proposed that uses the semantic similarity and the relatedness degree to represent the semantic relations between words. Word sense disambiguation is also performed in the built lexical chains. Experiments on Web news pages and journal articles show that the proposed keyword extraction method is effective. An example run of our PNFS system demonstrates the superiority of this Web intelligence system.
Xindong Wu is a Yangtze River Scholar in the School of Computer Science and Information Engineering at the Hefei University of Technology (China), a Professor of Computer Science at the University of Vermont (USA), and a Fellow of the IEEE and AAAS. He received his Bachelor's and Master's degrees in Computer Science from the Hefei University of Technology, China, and his Ph.D. degree in Artificial Intelligence from the University of Edinburgh, Britain. His research interests include data mining, knowledge-based systems, and Web information exploration.
Dr. Wu is the Steering Committee Chair of the IEEE International Conference on Data Mining (ICDM), the Editor-in-Chief of Knowledge and Information Systems (KAIS, by Springer), and an Editor-in-Chief of the Springer Book Series on Advanced Information and Knowledge Processing (AI&KP). He was the Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering (TKDE, by the IEEE Computer Society) between 2005 and 2008. He served as Program Committee Chair/Co-Chair for ICDM '03 (the 2003 IEEE International Conference on Data Mining), KDD-07 (the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), CIKM 2010 (the 19th ACM Conference on Information and Knowledge Management), and IEEE/ACM ASONAM '14 (the 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining).
He received the 2012 IEEE Computer Society Technical Achievement Award "for pioneering contributions to data mining and applications", and the 2014 IEEE ICDM 10-Year Highest-Impact Paper Award.
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Herbert Dawid
Title: Agent-based Simulation for the Analysis of Inequality Dynamics and Economic Policy Design
The talk will give a survey of recent work in the area of agent-based computational economics focussing on the potential of this approach for gaining a better understanding of mechanisms generating (income) ineqaulity in economic systems and for evaluating the implications of changes in economic policies and institutional setups. This potential will be illustrated using examples of macroeconomic agent-based models as well as such applied in labor market analysis. Furthermore, key challenges of this area of researach will be discussed, in particular new approaches for calibrating large agent-based models and providing them with strong behavioral and empirical foundations.
Herbert Dawid is currently Professor for Economic Theory and Computational Economics at the Department of Business Administration and Economics and at the Center for Mathematical Economics at Bielefeld University, Germany. His research interests can be summarized as Economic Dynamics, Agent-based Computational Economics, Economics of Innovation, Evolutionary Game Theory, and Dynamic Optimization. He has published one monograph and over 80 research papers in refereed journals and collected volumes, including Journal of Economic Theory, Journal of Economic Dynamics and Control, Games and Economic Behavior, Economic Theory, Journal of Economic Behavior and Organization, IEEE Transactions on Evolutionary Computation plus approximately 25 additional scientific journals in Economics, Operations Research and Computer Science. He is also the Co-Editor of the Journal of Economic Dynamics and Control, and an Associate Editor or editorial board member of Dynamic Games and Applications, Journal of Evolutionary Economic, and Springer Lecture Notes in Economics and Mathematical Systems.
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