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Sobre

Sobre

O Fábio nasceu em Lisboa, Portugal em 1988. Licenciou-se em Engenharia de Redes de Computadores e Multimédia em 2011 pelo Instituto Superior de Engenharia de Lisboa. Decidiu depois prosseguir os seus estudos, tendo ingressado no Mestrado em Engenharia Informática da Universidade do Minho, de onde obteve o grau de Mestre em 2013. Desde essa altura, o Fábio é invetigador no HASLab, Laboratório Associado do INESC TEC. Doutorou-se em 2018 no programa doutoral em informática MAP-i administrado em co-tutela pelas  Universidades do Minho, Aveiro e Porto. Conjuntamente, o seu trabalho de investigação e tese de doutoramento focam-se em ferramentas de "Data Analytics" para sistemas de larga escala, vulgo "BigData". De entre outros tópicos, o Fábio interessa-se também por sistemas de "Benchmarking" e por sistemas de processamento transacional distribuídos. Nos seus tempos livres, gosta de viajar e de fotografia.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Fábio André Coelho
  • Cargo

    Investigador Sénior
  • Desde

    01 janeiro 2014
010
Publicações

2024

Databases in Edge and Fog Environments : A Survey

Autores
Meruje Ferreira, LM; Coelho, F; Pereira, J;

Publicação
ACM Computing Surveys

Abstract
While a significant number of databases are deployed in cloud environments, pushing part or all data storage and querying planes closer to their sources (i.e., to the edge) can provide advantages in latency, connectivity, privacy, energy and scalability. This article dissects the advantages provided by databases in edge and fog environments, by surveying application domains and discussing the key drivers for pushing database systems to the edge. At the same time, it also identifies the main challenges faced by developers in this new environment, and analysis the mechanisms employed to deal with them. By providing an overview of the current state of edge and fog databases, this survey provides valuable insights into future research directions.

2024

Review of Commercial Flexibility Products and Market Platforms

Autores
Rodrigues, L; Ganesan, K; Retorta, F; Coelho, F; Mello, J; Villar, J; Bessa, R;

Publicação
International Conference on the European Energy Market, EEM

Abstract
The European Union is pushing its members states to implement regulations that incentivize distribution system operators to procure flexibility to enhance grid operation and planning. Since flexibility should be obtained using market-based solutions, when possible, flexibility market platforms become essential tools to harness consumer-side flexibility, supporting its procurement, trading, dispatch, and settlement. These reasons have led to the appearance of multiple flexibility market platforms with different structure and functionalities. This work provides a comprehensive description of the main flexibility platforms operating in Europe and provides a concise review of the platform main characteristics and functionalities, including their user segment, flexibility trading procedures, settlement processes, and flexibility products supported. © 2024 IEEE.

2024

GDBN, A Customer-centric Digital Platform to Support the Value Chain of Flexibility Provision

Autores
Coelho, F; Rodrigues, L; Mello, J; Villar, J; Bessa, R;

Publicação
International Conference on the European Energy Market, EEM

Abstract
This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders' engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios. © 2024 IEEE.

2023

Privacy-Preserving Machine Learning in Life Insurance Risk Prediction

Autores
Pereira, K; Vinagre, J; Alonso, AN; Coelho, F; Carvalho, M;

Publicação
MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2022, PT II

Abstract
The application of machine learning to insurance risk prediction requires learning from sensitive data. This raises multiple ethical and legal issues. One of the most relevant ones is privacy. However, privacy-preserving methods can potentially hinder the predictive potential of machine learning models. In this paper, we present preliminary experiments with life insurance data using two privacy-preserving techniques: discretization and encryption. Our objective with this work is to assess the impact of such privacy preservation techniques in the accuracy of ML models. We instantiate the problem in three general, but plausible Use Cases involving the prediction of insurance claims within a 1-year horizon. Our preliminary experiments suggest that discretization and encryption have negligible impact in the accuracy of ML models.

2023

Analysis of Flexibility-centric Energy and Cross-sector Business Models

Autores
Rodrigues, L; Faria, D; Coelho, F; Mello, J; Saraiva, JT; Villar, J; Bessa, RJ;

Publicação
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
The new energy policies adopted by the European Union are set to help in the decarbonization of the energy system. In this context, the share of Variable Renewable Energy Sources is growing, affecting electricity markets, and increasing the need for system flexibility to accommodate their volatility. For this reason, legislation and incentives are being developed to engage consumers in the power sector activities and in providing their potential flexibility in the scope of grid system services. This work identifies energy and cross-sector Business Models (BM) centered on or linked to the provision of distributed flexibility to the DSO and TSO, building on those found in previous research projects or from companies' commercial proposals. These BM are described and classified according to the main actor. The remaining actors, their roles, the interactions among them, how value is created by the BM activities and their value propositions are also described.

Teses
supervisionadas

2023

Communication-efficient P2P system for FL

Autor
Susana Vitória Sá Silva Marques

Instituição
INESCTEC

2023

MulletBench: Multi-layer Edge Time Series Database Benchmark

Autor
Pedro Pereira

Instituição
INESCTEC

2023

Towards Tunable Distributed Data Management for IoT

Autor
Luís Manuel Meruje Ferreira

Instituição
INESCTEC

2022

Gestão de permissões e acesso a dados para Hyperledger Fabric

Autor
João Pedro Araújo Parente

Instituição
INESCTEC

2022

Towards Tunable Distributed Data Management for IoT

Autor
Luís Manuel Meruje Ferreira

Instituição
INESCTEC