Archive for the ‘Agenda’ Category

By : Prof. Pang Nin Tan
Associate Professor in the Department of Computer Science and Engineering
At Michigan State University

Abstract:

Climate change due to human activities such as the burning of fossil fuels, deforestation, and certain land-use activities has become a subject of major concern among scientists, policymakers, environmental civic groups, and the public. Despite the importance of this issue, our ability to predict climate variability and to assess its impact on human and natural systems remains a great challenge. This talk presents my current research in the development of data mining algorithms to enhance pattern discovery and predictive modeling of Earth science data. First, I will describe a pattern discovery algorithm for detecting and characterizing ecosystem disturbances (wildfires, hurricanes, etc) from satellite-based vegetation cover data. I will then present a semi-supervised learning framework for improving long-term projection of future climate scenarios.

Biography:

Pang-Ning Tan is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S.degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests span a variety of areas in data mining, including pattern discovery in large databases, spatio-temporal data mining, semi-supervised learning, text mining, and link analysis. He has published more than ninety technical papers in journals, book chapters, and conferences. He is also the first author of the textbook “Introduction to Data Mining,” published by Addison Wesley in 2005. His book has been adopted for use in data mining courses offered at more than 100 universities throughout the United States and translated into Chinese and Korean (with translation to Greek and Portuguese in progress). He is currently the Associate Editor for IEEE Intelligent Informatics Bulletin and has served on the organizing committee and program committee for many international conferences.

Date & Venue
22 JULI 2009, WEDNESDAY
AULA FAKULTAS ILMU KOMPUTER UI
13.00 – 14.00 WIB

By Professor Oren Etzioni, PhD
Director of Turing Center & Professor of Computer Science
The University of Washington, USA

“Artificial Intelligence in a Moore’s Law World : The Stories of Farecast and KnowItAll”

ABSTRACT
What is the Role for Artificial Intelligence as CPUs, disks, and networks become exponentially more powerful?

Perhaps, as some have suggested, the application of simple processing techniques to unprecedented mountains of data will suffice for most applications. Could Luis von Ahn’s paradigm of “Human Computation” yield any additional intelligence that is required? In this talk I will argue, to the contrary, that Al techniques such as data mining and information extraction enable exciting new applications. But these techniques need to be improved in important ways. Etzioni will make these points through the stories his startup Farecast (a company that utilizes data mining techniques to anticipate airfare fluctuations and to inform consumers about the right time to buy their air tickets) and his academic research project, KnowItAll (the KnowItAll project has been developing a variety of domain-independent systems that extract infomation from the Web in an autonomous, scalable manner).

BIOGRAPHY :
Oren Etzioni is a Professor of Computer Science at the University of Washington’s Computer Science Department, and the founder and director of the university’s Turing Center. He received his Ph.D. from Carnegie Mellon in 1990, and his B.A. from Harvard in 1986. Etzioni has authored of over 100 technical papers on topics ranging from intelligent agents and natural-language interfaces to information extraction and Web search. In 2007, he received the Robert S. Engelmore Memorial Award for longstanding technical and entrepreneurial contributions to AI. In 2005, he was received the IJCAI Distinguished Paper Award, and in 2003 he was chosen as a AAAI Fellow.

Etzioni is the founder of three companies. In 2003, he founded Farecast , a company that utilizes data mining to inform consumers about the right time to buy their air tickets. His work has been featured in the New York Times, Wall Street Journal, NPR, SCIENCE, The Economist, TIME Magazine, Business Week, Newsweek, Discover Magazine, Forbes Magazine, Wired, and elsewhere.