SICSS-FGV/DAPP Brazil

June 14 to June 26, 2021 | FGV/DAPP | Virtual event

People


Faculty

Image of Marco Aurélio Ruediger
Marco Aurélio Ruediger
Marco Aurelio Ruediger is the Faculty Sponsor of SICSS FGV-DAPP Brazil. He holds a PhD in Sociology and is the Director of Public Policy Analysis of Fundação Getulio Vargas (FGV/DAPP). His main fields of interest are political sociology, communication, social networks, and technological innovation and its impacts on democracy. He is a consulting member of the D4D initiatives of the National Democratic Institute and Social Science One. He is currently leading the creation of the School of Communication, Media and Information of Fudação Getulio Vargas and of the project “Digitalization and Democracy in Brazil”, carried out with the support of the Ministry of Foreign Affairs of Germany and of the German Embassy in Brasília
Image of Tiago Ventura
Tiago Ventura
Tiago Ventura is a Ph.D. Candidate in Government and Politics at the University of Maryland, College Park (UMD), and an alumni of SICSS Princeton in 2019. Tiago is a researcher on comparative politics and computational social science, with a particular focus on political violence in Latin America and political communication. During the Winter and Spring of 2021, He will be the Young Talent fellow in Computational Social Science at FGV Rio de Janeiro. Tiago is also a researcher at the Interdisciplinary Laboratory for Computational Social Science at UMD.
Image of Amaro Grassi
Amaro Grassi
Amaro Grassi is a Ph.D. Candidate in Political Science at IESP-UERJ, and Chief Researcher at The Department of Public Policy Analysis of Getulio Vargas Foundation (FGV/DAPP)
Image of Danilo Carvalho
Danilo Carvalho
Danilo Carvalho is a Master student in Informatics at the Federal University of Rio de Janeiro (Brazil) and coordinator of Data Science at the Department of Public Policy Analysis of Getulio Vargas Foundation (Brazil). He works with the monitoring of online public debate, automated behavior detection, information spreading, and machine learning in applied social sciences.

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