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Learning and Mining in Complex Networks, with Applications to Cyber Situational Awareness

Date and Time
Tuesday, March 8, 2011 - 12:00pm to 1:00pm
Computer Science 302
Tina Eliassi-Rad, from Rutgers University
Complex networks are ubiquitous in many domains. Examples include spatial, technological, informational, social, and biological networks. In this talk, I will present algorithms for both network classification and clustering, paying specific attention to evaluation in such non-IID settings, scalability, transfer learning, and applications to cyber situational awareness.

Tina Eliassi-Rad is an Assistant Professor at the Department of Computer Science at Rutgers University. She is also a member of the Rutgers Center for Computational Biomedicine, Imaging, and Modeling (CBIM) and Rutgers Center for Cognitive Science (RuCCS). Until September 2010, Tina was a Member of Technical Staff at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison in 2001. Broadly speaking, Tina's research interests include machine learning, data mining, and artificial intelligence. Her work has been applied to the World-Wide Web, text corpora, large-scale scientific simulation data, and complex networks. Tina is an action editor for the Data Mining and Knowledge Discovery Journal. She received a US DOE Office of Science Outstanding Mentor Award in 2010.

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