Abstract
The lectures include the three centrality measures: degree centrality, closeness centrality and betweenness centrality. Degree centrality is discussed as a measure of success in a graph evolution model investigating the PhD-student-advisor network and the glass ceiling effect, both from a theoretical as well as a data point of view. The lectures also includes different influence networks, their convergence time, and convergence states.
Biography
Dr. Barbara Keller is a lecturer in the computer science department at Aalto University, Finland. Before her lectureship, she spent four years in industry developing a certification program for Nevis, a security suite used by the Swiss border control as well as by major Swiss banks, securing over 80% of all e-banking transactions in Switzerland. She did her PhD at ETH in the distributed computing group led by Prof. Roger Wattenhofer. During her PhD, she spent a year in the Weizmann Institute of Science under the supervision of David Peleg and acquired the didactics certificate for higher education from ETH. She did her Msc at ETH majoring in information security. Her research interest lies in network analysis and her recent work includes the analysis of social network phenomena and network algorithms.
