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About

Fábio Coelho (Male, PhD) is currently a senior researcher of HASLab, one of INESC TEC's research units. He holds a PhD in Computer Science, in the context of the MAP-i Doctoral Programme, from the universities of Minho, Aveiro and Porto (Portugal). His research is focused on cloud HTAP databases, cloud computing, distributed systems, P2P/ledger based systems and benchmarking. He has several international publications in top-tier conferences, such as SRDS, DAIS and ICPE. He participated in several national and EU projects such as CoherentPaaS, LeanBigData, CloudDBAppliance and Integrid. Currently he works closely with the Power and Energy Centre of INESC TEC in the provisioning of ICT solutions for coordination and distributed communication.

Interest
Topics
Details

Details

  • Name

    Fábio André Coelho
  • Cluster

    Computer Science
  • Role

    Assistant Researcher
  • Since

    01st January 2014
005
Publications

2022

AIDA-DB: A Data Management Architecture for the Edge and Cloud Continuum

Authors
Faria, N; Costa, D; Pereira, J; Vilaça, R; Ferreira, L; Coelho, F;

Publication
2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)

Abstract

2022

Towards a Cross-domain Semantically Interoperable Ecosystem

Authors
Tosic, M; Coelho, FA; Nouwt, B; Rua, DE; Tomcic, A; Pesic, S;

Publication
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining

Abstract

2021

Functional Scalability and Replicability Analysis for Smart Grid Functions: The InteGrid Project Approach

Authors
Menci, SP; Bessa, RJ; Herndler, B; Korner, C; Rao, BV; Leimgruber, F; Madureira, AA; Rua, D; Coelho, F; Silva, JV; Andrade, JR; Sampaio, G; Teixeira, H; Simoes, M; Viana, J; Oliveira, L; Castro, D; Krisper, U; Andre, R;

Publication
Energies

Abstract
The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at the earliest stage, i.e., during the pilot phase and before large-scale deployment and mass adoption. Therefore, this paper presents the scalability and replicability analysis conducted within the European project InteGrid. Within the project, innovative solutions are proposed and tested in real demonstration sites (Portugal, Slovenia, and Sweden) to enable the DSO as a market facilitator and to assess the impact of the scalability and replicability of these solutions when integrated into the network. The analysis presents a total of three clusters where the impact of several integrated smart tools is analyzed alongside future large scale scenarios. These large scale scenarios envision significant penetration of distributed energy resources, increased network dimensions, large pools of flexibility, and prosumers. The replicability is analyzed through different types of networks, locations (country-wise), or time (daily). In addition, a simple replication path based on a step by step approach is proposed as a guideline to replicate the smart functions associated with each of the clusters.

2021

Enabling Interoperable Flexibility and Standardized Grid Support Services

Authors
Falcão, J; Cândido, C; Silva, D; Sousa, J; Pereira, M; Rua, D; Gouveia, C; Coelho, F; Bessa, R; Lucas, A;

Publication
CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution

Abstract

2020

Self-tunable DBMS Replication with Reinforcement Learning

Authors
Ferreira, L; Coelho, F; Pereira, J;

Publication
Distributed Applications and Interoperable Systems - Lecture Notes in Computer Science

Abstract

Supervised
thesis

2021

Data Market for Energy Industry Forecasting

Author
Filipe Daniel Vieira da Silva

Institution
UM

2021

Query Optimizers Based on Machine Learning Techniques

Author
Rui Pedro Sousa Rodrigues do Souto

Institution
UM

2021

Towards Tunable Distributed Data Management for IoT

Author
Luís Manuel Meruje Ferreira

Institution
UM

2020

Automatic Parameter Tuning Using Reinforcement Learning

Author
Luís Manuel Meruje Ferreira

Institution
UM

2019

High Availability Architecture for Cloud Based Databases

Author
Hugo Miguel Ferreira Abreu

Institution
UM