March 16, 2018, Webb 1100

In this talk we study a novel methodology for estimating the social influence among agents interacting in a sparse social network described by the Friedkin and Johnsen’s model. In this classical model, n agents discuss m

Chiara Ravazzi received the B.Sc., M.Sc., and Ph.D. degrees from the Politecnico di Torino,Italy, in 2005, 2007, and 2011, respectively, all in applied mathematics. In 2010, she was a Visiting Member with the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge. From 2011 to 2012, she was a Research Assistant with the Department of Mathematics, Politecnico di Torino. From 2012 to 2016, she held a post-doctoral position with the Department of Electronics and Telecommunications, Politecnico di Torino, where she was involved in developing algorithms for sparse recovery problems, within the project Towards Compressive Information Processing Systems funded by the European Union as ERC starting grant (2012-2016). From 2013 to 2016, she was a Research Associate with the National Research Council of Italy (CNR), Institute of Electronics, Computer and Telecommunication Engineering (IEIIT). Since 2017, she has been a Tenured Researcher with the CNR-IEIIT, working in the Systems Modeling & Control Group. Her current research interests include signal processing, optimization and control of network systems.