Prof. Fabricio Murai Ferreira and Prof. Flavio Figueiredo
Period and Duration
From Jan 15 to Feb 05 (30 hours)
In this course, we shall explore data analysis and prediction using complex network datasets. In particular, our focus will be on temporal and structural data. Examples of datasets that will be explored can be found on the SNAP , ICON  and Koblenz  network repositories.
Course Programme and Schedule:
Each class is composed by 1.5 h of lectures and 1.5 h of hands on exercise.
|Date and Location
|Jan 15 14:00
|Intro to network science
|Jan 16 14:30
|Probabilistic network models
|Jan 17 14:00
|Jan 22 14:00
|Jan 23 14:00
|Graph node embeddings
|Jan 24 14:00
|Network analysis using n-dimensional data
|Jan 29 14:00
|Cascades and time series
|Jan 30 14:00
|Point processes on networks
|Jan 31 14:00
|Granger causality and covariance extraction
|Feb 05 14:00
During each class, a small programming assignment has to be accomplished by each student. As described above, we will explore real complex networks from popular repositories. Complementing these assignments, a class project must be presented in the final lecture.
Fabricio Murai Ferreira (born 20/11/1985) is an Assistant Professor in the Department of Computer Science at the Universidade Federal de Minas Gerais, Brazil. His research lies in the application of mathematical modeling, statistics and machine learning to computer, informational and social networks. In particular, his work focuses on partially observed networks. He obtained his B.Sc. degree (*magna cum laude*) from the Universidade Federal do Rio de Janeiro in 2007 and his Ph.D. degree under Professor Don Towsley from the University of Massachusetts Amherst in 2016, both in Computer Science. During his graduate studies, he received a number of awards including a 4-year scholarship from CNPq (Brazil’s National Research Council) and a 2013 UMass Amherst CS Outstanding Synthesis Award sponsored by Yahoo!. He has published in top scientific venues such as IEEE Journal of Selected Areas in Communications, Data Mining and Knowledge Discovery, IEEE INFOCOM, IEEE/ACM ASONAM etc. He serves as a TPC member for the IEEE INFOCOM and the IEEE/WIC/ACM Web Intelligence and has reviewed papers for important journals in his field.
Flavio Figueiredo (born 30/09/1985) is a professor at Universidade Federal de Minas Gerais (UFMG). He received his PhD and MSc degrees from the same university and his BSc from Universidade Federal de Campina Grande (UFCG). In the past, he was a visiting scholar at Carnegie Mellon University as well as the at the University of British Columbia. Flavio has also worked on industry research for a year at IBM’s Research Lab in Rio de Janeiro. Currently, he performs research developing and applying data science and machine learning algorithms for a wide range of contexts (from social media, Internet traces and cultural production). In particular, he is interested in understanding large scale social and cultural phenomena using online data. Flavio has published papers in prestigious conferences such as CHI, WWW, WSDM, ECML/PKDD, WebSci, and ISMIR.