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.
     
     

     
     
    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, Z├╝rich, 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