???global.info.a_carregar???
I see myself as a hardworking and dependable individual. I am highly motivated to acquire new knowledge as well as experience and grow as a result. Furthermore, I consider myself adaptable and communicative, and I strive to assist others with their problems. One of my core strengths is being demanding of myself. On the other hand, my biggest weakness is having to improvise, so I've developed good planning skills. My primary area of expertise is Artificial Intelligence (AI) applications in power systems, smart grids, and industrial/household environments. With a greater emphasis on improving energy efficiency, renewable energy use, demand response participation, bill savings, machine degradation, and product quality. On July 13, 2020, I completed my degree in Informatics Engineering at ISEP with a 17 out of 20 grade. Accordingly, I received a merit certificate in 2021 for being among the best students. Afterward, I completed my master's degree in AI Engineering at ISEP on November 15, 2022, with a 19 out of 20 grade (20 out of 20 on my master’s dissertation). I received the second-highest grade, and as a result, I received a best student merit certificate in 2023. From the start of my Informatics Engineering degree final project on 3 February 2020 up until 29 February 2024, I worked on GECAD as a researcher. My research focused on the development and improvement of a system capable of scheduling production lines by using a Genetic Algorithm. In addition, it also enabled the rescheduling of a previous plan to respond to demand response programs and machine breakdowns. Moreover, predictive maintenance using Machine Learning (ML) was also explored and implemented. During this time, I worked on two international European projects: SPEAR in 2020, and MUWO in 2021-2023. These international projects were an invaluable experience in my career, since they allowed me to collaborate with various businesses in the manufacturing sector, thereby improving my international dissemination skills and networking. For now, I have published 7 papers in scientific journals, 1 in book chapters, and 8 conference papers. Additionally, 2 manuscripts have been submitted. Regarding scientific journals, I have published in Energy (Elsevier, IF 9.00), Renewable Energy (Elsevier, IF 8.70), Energy Reports (Elsevier, IF 5.20), IEEE Access (IEEE Xplore, IF 3.56), Energy Informatics (Springer, IF 3.52), and Energies (MDPI, IF 3.20). A book chapter was published in the Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems book. My most relevant paper is a recently published work on residential load shifting for cost reduction (DOI:10.1016/j.energy.2022.124978), for which I was awarded a merit certificate in scientific publication. At the moment, since the beginning of March of 2024, I have been working on my PhD at USAL, which was awarded by the FCT and ranked first in Computer Science and Informatics among 147 candidates. The proposed PhD, titled “Towards Efficient and Fast-paced Manufacturing Production Lines by applying Automated Machine Learning Models with Explainable Artificial Intelligence for Knowledge Transfer”, focuses on the research, design, implementation, validation, and dissemination of easily deployable and interpretable ML models for manufacturing environments capable of improving a production line scheduling algorithm’s reliability and efficiency. It will achieve this by employing an Automated ML (AutoML) methodology in a manufacturing environment, for faster deployments of ML systems without the need for an expert, and eXplainable AI (XAI), to generate explanations for the model's actions. The main novelty of the PhD is the usage of ML models based on AutoML and using XAI to obtain knowledge that then can be applied in a production line scheduling algorithm, through knowledge transfer. My PhD is being carried out both in GECAD (ISEP), and BISITE (USAL).
Identification

Personal identification

Full name
Bruno Alexandre Santos Mota

Citation names

  • Bruno Mota
  • Mota, Bruno
  • B Mota

Author identifiers

Ciência ID
6019-8D23-F05A
ORCID iD
0000-0002-9875-4868
Google Scholar ID
https://scholar.google.com/citations?user=HmCz488AAAAJ&hl=pt-PT

Email addresses

  • bamoa@isep.ipp.pt (Professional)
  • 1171198@isep.ipp.pt (Professional)
  • brunomota19199@gmail.com (Personal)

Telephones

Mobile phone
  • 960451794 (Personal)

Addresses

  • Instituto Superior de Engenharia do Porto, R. Dr. António Bernardino de Almeida, 431, 4249-015, Porto, Porto, Portugal (Professional)

Websites

Knowledge fields

  • Exact Sciences - Computer and Information Sciences

Languages

Language Speaking Reading Writing Listening Peer-review
Portuguese (Mother tongue)
English Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2)
Education
Degree Classification
2024/03/01 - 2027/03/01
Ongoing
Doctorado en Ingeniería Informática (Doutoramento)
Universidad de Salamanca, Spain
"Towards Efficient and Fast-paced Manufacturing Production Lines by applying Automated Machine Learning Models with Explainable Artificial Intelligence for Knowledge Transfer" (THESIS/DISSERTATION)
2023/03/01 - 2023/12/15
Concluded
Investigação e Desenvolvimento em Engenharia (Pós-Graduação)
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
17
2020/10/06 - 2022/11/15
Concluded
Engenharia de Inteligência Artificial (Mestrado integrado)
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
"Joint Optimization of Production and Maintenance for Effective Manufacturing and Demand Response Participation" (THESIS/DISSERTATION)
19
2017/09/25 - 2020/07/13
Concluded
Engenharia Informática (Licenciatura)
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
"Planeamento/Escalonamento da Produção tendo em conta o Custo da Energia" (THESIS/DISSERTATION)
17
Affiliation

Science

Category
Host institution
Employer
2020/02/03 - Current Researcher (Research) Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
Projects

Grant

Designation Funders
2024/03/01 - Current Towards Efficient and Fast-paced Manufacturing Production Lines by applying Automated Machine Learning Models with Explainable Artificial Intelligence for Knowledge Transfer
2023.03776.BD
PhD Student Fellow
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal

Universidad de Salamanca, Spain
Fundação para a Ciência e a Tecnologia
Ongoing
2020/12/15 - 2021/07/31 GECAD-PES_2020-01
GECAD-PES_2020-01
Research Fellow
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Associação para a Inovação e Desenvolvimento da FCT

European Commission
Concluded

Contract

Designation Funders
2023/07/12 - 2024/02/29 PRODUTECH R3 - Recuperação-Resiliência-Reindustrialização
GECAD-PES_2023-08
Research Fellow
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Associação para a Inovação e Desenvolvimento da FCT
Concluded
2021/08/01 - 2023/07/11 Muwo - Multi-method workspace for highly scalable production lines
GECAD-PES_2021-07
Research Fellow
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Autoridade de Gestão do Programa Operacional Competitividade e Internacionalização
Concluded
2020/02/03 - 2020/12/14 SPEAR - Smart Prognosis of Energy with Allocation of Resources
GECAD_2019-11
Research Fellow
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Agência Nacional de Inovação SA

Associação para a Inovação e Desenvolvimento da FCT
Concluded
Outputs

Publications

Book chapter
  1. Bruno Mota; Tiago Pinto; Zita Vale; Carlos Ramos. "Deep Learning in Intelligent Power and Energy Systems". 45-67. Wiley, 2022.
    Published • 10.1002/9781119834052.ch3
Conference paper
  1. Bruno Mota; Pedro Faria; Carlos Ramos. "Production Plan Rescheduling for Machine Breakdown Events using a Genetic Algorithm". Paper presented in The 22nd IEEE Mediterranean Electrotechnical Conference (IEEE Melecon 2024), Porto, 2024.
    Submitted
  2. Bruno Mota; Pedro Faria; Carlos Ramos. "Machine Learning Applied to Industrial Machines for an Efficient Maintenance Strategy: A Predictive Maintenance Approach". Paper presented in The Energy Informatics.Academy Conference 2023 (EI.A 2023), São Paulo, 2023.
    Published • 10.1007/978-3-031-48649-4_17
  3. Bruno Mota; Daniel Ramos; Pedro Faria; Carlos Ramos. "Production Scheduling for Total Energy Cost and Machine Longevity Optimization Through a Genetic Algorithm". Paper presented in The 22nd Portuguese Conference on Artificial Intelligence (EPIA 2023), Faial Island, Azores, 2023.
    Published • 10.1007/978-3-031-49011-8_15
  4. Bruno Mota; Pedro Faria; Carlos Ramos. "Production Line Energy Cost Optimization with Renewable Energy Resource Usage in a Flexible Job Shop Configuration". Paper presented in The 22nd World Congress of the International Federation of Automatic Control (IFAC World Congress 2023), Yokohama, 2023.
    Published • 10.1016/j.ifacol.2023.10.918
  5. Bruno Mota; Pedro Faria; Bruno Canizes; Carlos Ramos. "Production and Maintenance Scheduling for Total Cost and Machine Longevity Optimization". Paper presented in International Conference on Future Energy Solutions (FES2023), Vaasa, 2023.
    Published • 10.1109/FES57669.2023.10183219
  6. Bruno Mota; Pedro Faria; Carlos Ramos. "Joint Optimization of Production and Maintenance for Effective Manufacturing Using a Genetic Algorithm". Paper presented in 23rd EEEIC International Conference on Environment and Electrical Engineering (EEEIC2023), Madrid, 2023.
    Published • 10.1109/EEEIC/ICPSEurope57605.2023.10194698
  7. Bruno Mota; Pedro Faria; Carlos Ramos. "Predictive Maintenance for Maintenance-Effective Manufacturing Using Machine Learning Approaches". Paper presented in International Workshop on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), Spain, 2022.
    Published • 10.1007/978-3-031-18050-7_2
  8. Bruno Mota; Miguel Albergaria; Helder Pereira; José Silva; Luis Gomes; Zita Vale; Carlos Ramos. "Climatization and luminosity optimization of buildings using genetic algorithm, random forest, and regression models". Paper presented in The Energy Informatics.Academy Conference 2021 (EI.A 2021), 2021.
    Published • 10.1186/s42162-021-00151-x
  9. João Muller; Bruno Mota; Carlos Ramos; Carlos Aita. "Utilização de Algoritmos Genéticos para Planeamento de Processos de Maquinação num Torno". Paper presented in Simpósio de Engenharia Informática 2020 (SEI 2020), Porto, 2020.
    Published
Journal article
  1. Bruno Mota; Pedro Faria; Zita Vale. "Energy cost optimization through load shifting in a photovoltaic energy-sharing household community". Renewable Energy 221 (2024): 119812. https://doi.org/10.1016/j.renene.2023.119812.
    Open access • Published • 10.1016/j.renene.2023.119812
  2. Bruno Mota; Pedro Faria; Carlos Ramos. "Integration of Production, Maintenance, and Quality in Manufacturing: A Review on Artificial Intelligence Techniques". Engineering Applications of Artificial Intelligence (2024):
    Submitted
  3. Bruno Mota; Pedro Faria; Carlos Ramos. "Joint Production and Maintenance Scheduling for Total Cost and Machine Overload Reduction in Manufacturing: A Genetic Algorithm Approach". IEEE Access 11 (2023): 98070-98081. https://doi.org/10.1109/ACCESS.2023.3312557.
    Published • 10.1109/ACCESS.2023.3312557
  4. Bruno Mota; Pedro Faria; Carlos Ramos. "Machine Overstrain Prediction for Early Detection and Effective Maintenance: A Machine Learning Algorithm Comparison". SOCO 2022 Special Issue - Logic Journal of the IGPL (2023):
    In press
  5. Bruno Mota; Pedro Faria; Zita Vale. "Residential load shifting in demand response events for bill reduction using a genetic algorithm". Energy (2022): https://doi.org/10.1016/j.energy.2022.124978.
    Published • 10.1016/j.energy.2022.124978
  6. Bruno Canizes; Bruno Mota; Pedro Ribeiro; Zita Vale. "Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting". IEEE Access 10 (2022): 62183-62193. https://doi.org/10.1109/ACCESS.2022.3182580.
    Published • 10.1109/ACCESS.2022.3182580
  7. Bruno Mota; Luis Gomes; Pedro Faria; Carlos Ramos; Zita Vale; Regina Correia. "Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events". Energies 14 2 (2021): 462-462. http://dx.doi.org/10.3390/en14020462.
    Published • 10.3390/en14020462
  8. Carlos Ramos; Rúben Barreto; Bruno Mota; Luis Gomes; Pedro Faria; Zita Vale. "Scheduling of a textile production line integrating PV generation using a genetic algorithm". Energy Reports 6 (2020): 148-154. https://doi.org/10.1016/j.egyr.2020.11.093.
    Published • 10.1016/j.egyr.2020.11.093
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2023/07/13 Production Line Energy Cost Optimization with Renewable Energy Resource Usage in a Flexible Job Shop Configuration The 22nd World Congress of the International Federation of Automatic Control (IFAC World Congress 2023)
Pacifico Yokohama (Yokohama, Japan)
2023/06/09 Joint Optimization of Production and Maintenance for Effective Manufacturing Using a Genetic Algorithm 23rd EEEIC International Conference on Environment and Electrical Engineering (EEEIC2023)
University Carlos III of Madrid Puerta de Toledo Campus (Madrid, Spain)
2022/09/14 Machine Learning Applied to Industrial Machines for An Efficient Maintenance Strategy: A Predictive Maintenance Approach The 9th International Conference on Energy and Environment Research (ICEER 2022)
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto (Porto, Portugal)
2020/11/27 Como incorporar em Sistemas de IA conhecimento humano sobre Controlo de Aparelhos de Climatização e Luminosidade? 1º Demo Day - Edição 2020
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto (Porto, Portugal)
Distinctions

Award

2023 Diploma de Mérito - Mestrado em Engenharia de Inteligência Artificial
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2023 Diploma de Melhor Estudante - Mestrado em Engenharia de Inteligência Artificial
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2022 Certificado de Mérito de Publicação Científica
Instituto Politécnico do Porto, Portugal
2021 Diploma de Mérito - Licenciatura em Engenharia Informática
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal