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About

About

Fernando Silva is currently a Professor of Computer Science at the Faculty of Sciences, University of Porto (FCUP), Department of Computer Science. He studied Applied Mathematics at the University of Porto (UP) and obtained his PhD in Computer Science from the University of Manchester, UK (1993). In 2007, obtained the Habilitation in Informatics from the New University of Lisbon. From 2018 to 2022, he served as Vice-Rector of the University of Porto responsible for the Digital University, Quality and Continuous Improvement. He currently is a member of the Scientific Council of FCUP and a member of the MAP-i of the scientific board of MAP-i doctoral program.


He founded in 2007 the Center for Research in Advanced Computing Systems (CRACS) which he led until 2018. From 2007 to 2018, he was a member of the scientific board of the Doctoral Program in Computer Science of the Universities of Minho, Aveiro, and Porto (MAP-i), being Director in 2008/09 and 2013/14. From 2007 to 2018, he was PI for the Dual PhD Degree in Computer Science between MAP-i and Carnegie Mellon University, representing UP, and between 2014 and 2017 was Co-Director for Advanced Computing in the UTAustin-Portugal initiative. He was head of the Computer Science Department in 2006 and 2007. From 2014 to 2018, he served as a member of the Scientific Council and the Representatives Council of FCUP. He also served on the first Ethics Committee of the University of Porto (2008/12), representing the sub-committee for the exact sciences and technologies.


His primary research interests are in parallel and distributed computing, mobile edge clouds, programming languages, algorithms for motif discovery in complex networks, and applications in information mining. He has advised 14 completed PhD theses in these areas. He has been invited to scientific committees of several workshops and conferences, was the general chair of the ICLP'2007, program chair of IBERGRID'2008, and was general and program chair of Euro-Par'2014. From 2017 to 2022 he was Vice-Chair of the Steering Committee of Euro-Par and has been the elected Chair since 2022. He has co-authored over 120 research publications and has led research projects totaling over 4 million euros, and also led digital transformation projects at UP totaling over 10 million euros. He is the scientific leader of Authenticus (www.authenticus.pt) a national publications metadata repository that uses identification algorithms to associate publications with researchers and institutions.

Interest
Topics
Details

Details

  • Name

    Fernando Silva
  • Role

    Research Coordinator
  • Since

    01st January 2009
  • Nationality

    Portugal
  • Contacts

    +351220402963
    fernando.silva@inesctec.pt
005
Publications

2024

Multilayer quantile graph for multivariate time series analysis and dimensionality reduction

Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, F;

Publication
INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS

Abstract
In recent years, there has been a surge in the prevalence of high- and multidimensional temporal data across various scientific disciplines. These datasets are characterized by their vast size and challenging potential for analysis. Such data typically exhibit serial and cross-dependency and possess high dimensionality, thereby introducing additional complexities to conventional time series analysis methods. To address these challenges, a recent and complementary approach has emerged, known as network-based analysis methods for multivariate time series. In univariate settings, quantile graphs have been employed to capture temporal transition properties and reduce data dimensionality by mapping observations to a smaller set of sample quantiles. To confront the increasingly prominent issue of high dimensionality, we propose an extension of quantile graphs into a multivariate variant, which we term Multilayer Quantile Graphs. In this innovative mapping, each time series is transformed into a quantile graph, and inter-layer connections are established to link contemporaneous quantiles of pairwise series. This enables the analysis of dynamic transitions across multiple dimensions. In this study, we demonstrate the effectiveness of this new mapping using synthetic and benchmark multivariate time series datasets. We delve into the resulting network's topological structures, extract network features, and employ these features for original dataset analysis. Furthermore, we compare our results with a recent method from the literature. The resulting multilayer network offers a significant reduction in the dimensionality of the original data while capturing serial and cross-dimensional transitions. This approach facilitates the characterization and analysis of large multivariate time series datasets through network analysis techniques.

2023

Jay: A software framework for prototyping and evaluating offloading applications in hybrid edge clouds

Authors
Silva, J; Marques, ERB; Lopes, LMB; Silva, FMA;

Publication
SOFTWARE-PRACTICE & EXPERIENCE

Abstract
We present Jay, a software framework for offloading applications in hybrid edge clouds. Jay provides an API, services, and tools that enable mobile application developers to implement, instrument, and evaluate offloading applications using configurable cloud topologies, offloading strategies, and job types. We start by presenting Jay's job model and the concrete architecture of the framework. We then present the programming API with several examples of customization. Then, we turn to the description of the internal implementation of Jay instances and their components. Finally, we describe the Jay Workbench, a tool that allows the setup, execution, and reproduction of experiments with networks of hosts with different resource capabilities organized with specific topologies. The complete source code for the framework and workbench is provided in a GitHub repository.

2023

MHVG2MTS: Multilayer Horizontal Visibility Graphs for Multivariate Time Series Analysis

Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, FMA;

Publication
CoRR

Abstract

2022

Network Science - 7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8-11, 2022, Proceedings

Authors
Ribeiro, P; Silva, F; Ferreira Mendes, JF; Laureano, RD;

Publication
NetSci-X

Abstract

2022

Preface

Authors
Ribeiro, P; Silva, F; Mendes, JF; Laureano, R;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

Supervised
thesis

2021

Web Search Engines - A study on the evolution of user interfaces

Author
Bruno Edgar Évora Rebelo Oliveira

Institution
UP-FEUP

2021

Adaptive Computation Offloading in Mobile Edge Clouds

Author
Joaquim Magalhães Esteves da Silva

Institution
UP-FCUP

2021

Uma solução de Business Intelligence para a área de recursos humanos da U.Porto

Author
Solange Sampaio Perdigão

Institution
UP-FCUP

2021

Uma solução de Business Intelligence para a área académica da U. Porto

Author
André lage Sobral

Institution
UP-FCUP

2021

A Predictive Analysis of Academic Success at Universidade do Porto

Author
Rafael António Belokurows

Institution
UP-FCUP