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The Role of Knowledge in Population Adaptation in Social Network Analysis

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  • Fri, 03/10/2017 - 11:00am - 12:00pm

Computer Science Colloquium Series
Dr. Pooya Moradian Zadeh

Date:  Friday, March 10th, 2017
Time: 11:00 am
Location: Chrysler Hall North, G100

Abstract: Social networks can be studied from different aspects- micro and macro. If we assume that the primary asset of each network is its population and the key difference between populations is their knowledge, then it is the knowledge that drives the evolution of these networks. Investigating the role of knowledge in the process of individual adaptation is the subject of this talk.

The main question here is to find out how a population can perform in different environments when it has a prior knowledge about the similar environment? Moreover, to what level of similarity between two networks, migrated population can be adapted efficiently? We define this concept as an adaptation process. The result of this research can lead to a remarkable reduction in the search time and space throughout the multiple steps of dynamic social network analysis.

Bio: I have recently defended my Ph.D. dissertation under the supervision of Dr. Ziad Kobti in the School of Computer Science at the University of Windsor. My research interests focus on the evolution of complex dynamic systems, particularly in social network analysis with emphasis on the role of underlying knowledge in the evolution process. The ultimate goal of my research studies is to employ graph theories, network science, and optimization methods to make a computational intelligence framework for describing the functionality of the complex dynamic social systems with the capability of exploring their behaviors.

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