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João Antunes Rodrigues holds a Bachelor's and Master's degree in Industrial Engineering and Management from ISEC (Instituto Superior de Engenharia de Coimbra). He furthered his academic journey by obtaining a PhD in Industrial Engineering and Management from UBI (University of Beira Interior). He has taught at the Coimbra Instituto Superior de Engenharia de Coimbra. He currently teaches at Universidade Lusófona and also contributes to the academic community by publishing numerous international scientific articles. He is currently an integrated researcher at RCM2+( Research Centre for Asset Management and Systems Engineering) and a collaborating researcher at CISE (Research Centre for Electromechatronic Systems).
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Identification

Personal identification

Full name
João Carlos Antunes Rodrigues

Citation names

  • Rodrigues, João Antunes
  • João C. Antunes Rodriges

Author identifiers

Ciência ID
8C11-27D7-A19A
ORCID iD
0000-0002-8210-5468
Education
Degree Classification
2023
Concluded
 Engenharia e Gestão Industrial (Doutoramento)
Universidade da Beira Interior, Portugal
"A Predictive Maintenance Model based on Multivariate Analysis with Artificial Intelligence" (THESIS/DISSERTATION)
2019
Concluded
 Engenharia e Gestão Industrial (Mestrado integrado)
Instituto Politécnico de Coimbra Instituto Superior de Engenharia de Coimbra, Portugal
2018
Concluded
 Engenharia e Gestão Industrial (Licenciatura)
Instituto Politécnico de Coimbra Instituto Superior de Engenharia de Coimbra, Portugal
2014
Concluded
 Manutenção Eletromecânica (Curso de Especialização Tecnológica)
Instituto Politécnico de Coimbra Instituto Superior de Engenharia de Coimbra, Portugal
Affiliation

Science

Category
Host institution 		Employer
2023/06/01 - Current Researcher (Research) Universidade Lusófona de Humanidades e Tecnologias, Portugal
RCM2+ Centro de Investigação em Gestão de Ativos e Engenharia de Sistemas, Portugal
2020/01/01 - Current Researcher (Research) Universidade da Beira Interior, Portugal
CISE - Electromechatronic Systems Research Centre, Portugal

Teaching in Higher Education

Category
Host institution 		Employer
2024 - Current Assistant Professor (University Teacher) Universidade Lusófona de Humanidades e Tecnologias, Portugal
2021 - Current Assistant (University Teacher) Universidade Lusófona de Humanidades e Tecnologias, Portugal
2019 - Current Tutor (University Teacher) Universidade Lusófona de Humanidades e Tecnologias, Portugal
Projects

Contract

Designation Funders
2023 - Current Earth Observation for Early Warning of Land Degradation at European Frontier
101086250
Researcher
Ongoing
2023 - Current "Creation of innovative ""humidity to electricity"" renewable energy conversion technology towards sustainable energy challenge"
101046307
2019/11/01 - 2023/10/31 Self-sufficient humidity to electricity Innovative Radiant Adsorption System Toward Net Zero Energy Buildings
871284
10.3030/871284
 European Commission
Concluded
Outputs

Publications

Journal article
  1. Alexandre Martins; Balduíno Mateus; Inácio de Sousa Adelino da Fonseca; José Torres Farinha; João Carlos Antunes Rodrigues; Mateus Mendes; Cardoso, A. J. M.. "Predicting the Health Status of a Pulp Press Based on Deep Neural Networks and Hidden Markov Models". Energies (2023): https://www.mdpi.com/1996-1073/16/6/2651.
    10.3390/en16062651
  2. João Carlos Antunes Rodrigues; Alexandre Martins; Mateus Mendes; José Torres Farinha; Ricardo Mateus; Cardoso, A. J. M.. "Automatic Risk Assessment for an Industrial Asset Using Unsupervised and Supervised Learning". Energies 15 24 (2022): 9387-9387. http://dx.doi.org/10.3390/en15249387.
    10.3390/en15249387
  3. João Carlos Antunes Rodrigues. "Comparison of Different Features and Neural Networks for Predicting Industrial Paper Press Condition". Energies 15 17 (2022): 6308-6308. http://dx.doi.org/10.3390/en15176308.
    10.3390/en15176308
  4. "Short and long forecast to implement predictive maintenance in a pulp industry". Eksploatacja I Niezawodnosc - Maintenance and Reliability (2021): http://www.ein.org.pl/sites/default/files/2022-01-05.pdf.
    10.17531/ein.2022.1.5
  5. "Predicting motor oil condition using artificial neural networks and principal component analysis". Eksploatacja i Niezawodnosc - Maintenance and Reliability (2020): http://dx.doi.org/10.17531/ein.2020.3.6.
    10.17531/ein.2020.3.6
Distinctions

Award

2021 Award for best presentation at international conference – TEPEN 2021& IncoME-VI, China.
2021 2nd place in the Young Engineer Innovation Award - PIJE 2021 (Ordem dos Engenheiros)
Ordem dos Engenheiros, Portugal