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Freie Universität Bozen

Lehrbeauftragte | High Performance Computing Lab

Flavio Vella

Flavio.Vella@unibz.it

+39 0471 016153

Fakultät für Informatik
Dominikanerplatz 3
39100
Bozen
Sprechstunden
Montag, 09:00 - 16:00
Dienstag, 09:00 - 18:00
Mittwoch, 09:00 - 18:00
Donnerstag, 09:00 - 18:00
Freitag, 09:00 - 17:00

Short bio

Dr. Flavio Vella is a tenure-track assistant professor at the University of Trento.  
His research interests include parallel computing, graph analysis and scalable machine learning with an emphasis on GPU programming and Big-Data. 
Previously, he had industry experience as a Research Engineer at Dividiti (UK) and as an intern at Nvidia (US). 
He was also visiting researcher at Scalable Computing Lab at ETH and a Post-Doc at National Research Council of Italy (CNR) and Assistant Professor at Free University of Bozen.
Dr. Vella, is also an active member of artifact evaluation initiatives for premier venues such as PPoPP, Computing Frontiers and [email protected] SC. /Dr. Flavio Vella is a tenure-track assistant professor at the University of Trento.  
His research interests include parallel computing, graph analysis and scalable machine learning with an emphasis on GPU programming and Big-Data. 
Previously, he had industry experience as a Research Engineer at Dividiti (UK) and as an intern at Nvidia (US). 
He was also visiting researcher at Scalable Computing Lab at ETH and a Post-Doc at National Research Council of Italy (CNR) and Assistant Professor at Free University of Bozen.
Dr. Vella, is also an active member of artifact evaluation initiatives for premier venues such as PPoPP, Computing Frontiers and [email protected] SC. 

Lehrveranstaltungen

Introduction to Parallel Computing

73049 · INF/01 · Master in Computational Data Science · EN

Parallel computing

76085 · INF/01 · Master in Software Engineering für Informationssysteme · EN

Forschungsschwerpunkte

Parallel and Distributed Computing;
GPU Computing;
Graph Analytics;
Machine Learning applied to HPC;
Scalable Machine Learning;
Performance Modeling./Calcolo Parallelo e Distribuito;
Calcolo su GPU;
Algoritmi per grafi di grandi dimensioni;
Tecniche di Machine Learning per applicazioni ad alte prestazioni 

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