Monday March 13th 4:00 - 4:50pm KEC 1001
Xiaoli Fern Assistant Professor School of EECS Oregon State University Data Mining for Ecosystem Informatics Ecosystem Informatics is an interdisciplinary field that examines the prospects for advancing computer science and information technology research by focusing on the complex and often unique challenges found in ecosystem domains. In the first part of this talk, I will present an overview of this emerging field and the critical challenges that data mining faces in this field. In the second part, I will present my research on unsupervised pattern discovery for two environmental science problems. For the first problem, clustering remote sensing land cover data, I will present an ensemble based clustering technique, which provides a flexible and reliable solution to the high dimensionality problem we face. For the second problem, correlation pattern analysis of vegetation-precipitation data, I will introduce a novel approach to learning mixtures of local linear correlation models that is capable of finding nonlinear correlation patterns, and patterns that are only locally valid in the data. Biography: Dr. Xiaoli Fern is an Assistant Professor of Computer Science at Oregon State University. She received her Ph.D (2005) in Computer Engineering from Purdue University and her M.S.(2000) and B.S.(1997) degrees from Shanghai Jiao Tong University. Her research interests are in machine learning and data mining, specifically in the area of unsupervised learning, including clustering, correlation analysis, dimension reduction, outlier detection and frequent pattern mining, etc. She is particularly interested in working with ecological and environmental data. _______________________________________________ Colloquium mailing list [email protected] https://secure.engr.oregonstate.edu/mailman/listinfo/colloquium
