Thu, 03.03.2016

Complex networks: From structure to dynamics

Dr. Olivia Woolley

ETH Zurich, Switzerland

 
In this course we will study the basic mathematical and computational methods used in the study of complex networks.
 
We will first discuss basic measures used to characterize network structure and the role of individual components in networks. This will include different centrality measures and community detection algorithms. We will then review standard network models and how their properties relate to real world networks, such as transportation, social and information networks. We will continue onto basic network optimization problems, such as shortest-path and searching algorithms.
 
Our main focus will be on exploring the connection between network structure and 1) network resilience, 2) dynamics on networks (focusing on spreading processes). We will also discuss the problem of inferring networks from available data. Finally Students will carry out a small project, visualizing and analyzing the properties of real networks to become familiar with some of the basic tools for network analysis.
 
 

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Short Profile

 
Education:

Northwestern University, Evanston, IL, USA
Ph.D. in Engineering Science and Applied Mathematics (ESAM), 2013
M.S. in Engineering Science and Applied Mathematics, 2007

Stanford University, Stanford, CA, USA
B.S. in Mathematical and Computational Science (Minor in Civil & Environmental Engineering), 2004
 
Research experience:

ETH, Zürich, Switzerland
Postdoctoral Research Fellow, Professorship of Computational Social Science 6/2013-present

Northwestern University, Evanston, IL, USA
PhD Researcher, ESAM and Northwestern Institute on Complex Systems 9/2007-5/2013

International Water Management Institute (IWMI), Colombo, Sri Lanka
Research and Analyst Consultant 5/2005-7/2006