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Daniel Ramos holds a bachelor's degree in Computer Engineering from the Institute of Engineering in Polytechnic of Porto - ISEP (2019) and a master's degree in Modeling, Data Analysis and Decision Support Systems at the Faculty of Economics of the University of Porto - FEP (2021). He has completed his master's thesis in the area of multi-agent systems with reinforcement learning for forecasting electricity consumption. He is currently doing a PhD in Informatics Engineering in University of Salamanca. The PhD thesis that he is currently developing consists on the following proposal "Explainable Collective Intelligence in Multi-Agent Systems with Learning Agents applied to Sustainable and Efficient Energy Systems". Since September 2019 he has been carrying out scientific research work within the scope of a research grant for graduates. This grant is developed within the scope of the research unit Research Group in Engineering and Intelligent Computing for Innovation and Development (GECAD), an ISEP unit classified as excellent by the FCT, within the framework of the DOMINOES project - Smart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services, funded by the European Commission under the HORIZON 2020 Program (H2020 Grant agreement ID: 771066). As a result of his scientific activities, he published 17 articles, 9 of which in international scientific journals and 8 in international scientific congresses. In 2019 he was a fellow of the LAPASSION project - Latin-America Practices and Soft Skills for an Innovation Oriented Network (585687-EPP-1-2017-1-PT-EPPKA2-CBHE-JP) of the Erasmus+ Capacity Building for Higher Education program, having carried out a 10-week mobility at the Instituto Federal do Maranhão, Brazil where he developed a multidisciplinary project with students from several countries (Brazil, Chile, Spain, Finland, Portugal and Uruguay). As part of this scholarship, he developed a system with a view to increasing the Human Development Index (HDI) of the state of Maranhão, focusing on the area of tourism, using the design thinking methodology.
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Identificação

Identificação pessoal

Nome completo
Daniel Carlos do Vale Ramos

Nomes de citação

  • Ramos, Daniel
  • D Ramos
  • Daniel Ramos

Identificadores de autor

Ciência ID
F014-3581-880B

Domínios de atuação

  • Ciências Exatas - Ciências da Computação e da Informação

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Português (Idioma materno)
Inglês Utilizador independente (B2) Utilizador independente (B2) Utilizador independente (B2) Utilizador independente (B2) Utilizador independente (B2)
Formação
Grau Classificação
2022 - 2025
Em curso
 Ingeniería informática (Doutoramento)
Universidad de Salamanca, Espanha

Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
2019/09/21 - 2021/11/08
Concluído
 Mestrado em Modelação, Análise de Dados e Sistemas de Apoio à Decisão (Mestrado)
Universidade do Porto Faculdade de Economia, Portugal
 17
2015/09/23 - 2019/02/12
Concluído
 Licenciatura em Engenharia Informática (Licenciatura)
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
 14
Percurso profissional

Ciência

Categoria Profissional
Instituição de acolhimento 		Empregador
2019/09/23 - 2023/02/28 Investigador (Investigação) Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
Projetos

Bolsa

Designação Financiadores
2021/10/22 - Atual RETINA (REal-Time support Infrastructure and Energy management for Intelligent carbon-Neutral smArt cities, NORTE-01-0145-FEDER-000062)
GECAD-PES_2021-14
Bolseiro de Investigação
Em curso

Projeto

Designação Financiadores
2019/09/23 - 2021/10/21 DOMINOES - Smart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services
771066
Bolseiro de Investigação
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal
European Commission
Concluído
2019/03/01 - 2019/05/31 LAPASSION - Latin-America Practices and Soft Skills for an Innovation Oriented Network
585687-EPP-1-2017-1-PT-EPPKA2-CBHE-JP
Bolseiro de Investigação
Instituto Politécnico do Porto, Portugal
 European Commission
Em curso
Produções

Publicações

Artigo em conferência
  1. Daniel Ramos; Pedro Faria; Luís Gomes; Vale, Zita. "CPU computation influence on energy consumption forecasting activities of a building". Trabalho apresentado em 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2024.
  2. Daniel Ramos; Pedro Faria; Luís Gomes; Vale, Zita. "Computational approaches for green computing of energy consumption forecasting on non-working periods in an office building". Trabalho apresentado em Energy Informatics, 2024.
  3. Ramos, Daniel; Faria, Pedro; Vale, Zita. "Analysis of the Consumption and Sensors Features Contribution to the Consumption Forecast Using Explainable AI in Buildings". 2024.
  4. Daniel Ramos; Pedro Faria; Luís Gomes; Vale, Zita. "Building Energy Consumption Forecast under Different Anticipations on a Green Computation Perspective". Trabalho apresentado em IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe, 2024.
  5. Daniel Ramos; Pedro Faria; Luís Gomes; Pedro Campos; Zita Vale. "A Learning Approach to Improve the Selection of Forecasting Algorithms in an Office Building in Different Contexts". Trabalho apresentado em EPIA, 2024.
  6. Daniel Ramos; Pedro Faria; Vale, Zita. "Comparison of Inputs Correlation and Explainable Artificial Intelligence Recommendations for Neural Networks Forecasting Electricity Consumption". Trabalho apresentado em Energy Informatics, 2024.
  7. Ramos, Daniel; Faria, Pedro; Vale, Zita. "Multi-agent Decision System in a Building to Coordinate the Energy Forecasting Tasks". 2024.
  8. Ramos, Daniel; Faria, Pedro; Gomes, Luis; Vale, Zita. "Energy Forecast in Buildings Addressing Computation Consumption in a Green Computing Approach". Trabalho apresentado em IEEE International Conference on Environment and Electrical Engineering, 2022.
    10.1109/eeeic/icpseurope54979.2022.9854723
  9. Ramos, Daniel; Faria, Pedro; Vale, Zita; Correia, Regina. "Electricity Consumption Forecast in an Industry Facility to Support Production Planning Update in Short Time". 2020.
    10.1109/eeeic/icpseurope49358.2020.9160535
Artigo em revista
  1. Ramos, D.; Faria, P.; Gomes, L.; Campos, P.; Vale, Z.. "Selection of features in reinforcement learning applied to energy consumption forecast in buildings according to different contexts". Energy Reports 8 (2022): 423-429. http://dx.doi.org/10.1016/j.egyr.2022.01.047.
    10.1016/j.egyr.2022.01.047
  2. Ramos, D.; Faria, P.; Morais, A.; Vale, Z.. "Using decision tree to select forecasting algorithms in distinct electricity consumption context of an office building". Energy Reports 8 (2022): 417-422. http://dx.doi.org/10.1016/j.egyr.2022.01.046.
    10.1016/j.egyr.2022.01.046
  3. Ramos, Daniel; Faria, Pedro; Vale, Zita; Correia, Regina. "Short Time Electricity Consumption Forecast in an Industry Facility". IEEE Transactions on Industry Applications 58 1 (2022): 123-130. http://dx.doi.org/10.1109/tia.2021.3123103.
    10.1109/tia.2021.3123103
  4. Vale, Zita; Gomes, Luis; Ramos, Daniel; Faria, Pedro. "Green computing: a realistic evaluation of energy consumption for building load forecasting computation". Journal of Smart Environments and Green Computing 2 2 (2022): 34-45. http://dx.doi.org/10.20517/jsegc.2022.06.
    10.20517/jsegc.2022.06
  5. Ramos, Daniel; Faria, Pedro; Gomes, Luis; Vale, Zita. "A Contextual Reinforcement Learning Approach for Electricity Consumption Forecasting in Buildings". IEEE Access 10 (2022): 61366-61374. http://dx.doi.org/10.1109/access.2022.3180754.
    10.1109/access.2022.3180754
  6. Ramos, Daniel; Khorram, Mahsa; Faria, Pedro; Vale, Zita. "Load Forecasting in an Office Building with Different Data Structure and Learning Parameters". Forecasting 3 1 (2021): 242-255. http://dx.doi.org/10.3390/forecast3010015.
    Acesso aberto • 10.3390/forecast3010015
  7. Ramos, Daniel; Teixeira, Brigida; Faria, Pedro; Gomes, Luis; Abrishambaf, Omid; Vale, Zita. "Using diverse sensors in load forecasting in an office building to support energy management". Energy Reports 6 (2020): 182-187. http://dx.doi.org/10.1016/j.egyr.2020.11.100.
    Acesso aberto • 10.1016/j.egyr.2020.11.100
  8. Ramos, Daniel; Faria, Pedro; Vale, Zita; Mourinho, João; Correia, Regina. "Industrial Facility Electricity Consumption Forecast Using Artificial Neural Networks and Incremental Learning". Energies 13 18 (2020): 4774. http://dx.doi.org/10.3390/en13184774.
    Acesso aberto • 10.3390/en13184774
  9. Ramos, Daniel; Teixeira, Brigida; Faria, Pedro; Gomes, Luis; Abrishambaf, Omid; Vale, Zita. "Use of Sensors and Analyzers Data for Load Forecasting: A Two Stage Approach". Sensors 20 12 (2020): 3524. http://dx.doi.org/10.3390/s20123524.
    Acesso aberto • 10.3390/s20123524
Capítulo de livro
  1. Mota, Bruno; Ramos, Daniel; Faria, Pedro; Ramos, Carlos. "Production Scheduling for Total Energy Cost and Machine Longevity Optimization Through a Genetic Algorithm". In Progress in Artificial Intelligence, 182-194. Springer Nature Switzerland, 2023.
    10.1007/978-3-031-49011-8_15
  2. Pinto, Tiago; Gomes, Luis; Faria, Pedro; Vale, Zita; Teixeira, Nuno; Ramos, Daniel. "Intelligent Simulation and Emulation Platform for Energy Management in Buildings and Microgrids". In Machine Learning for Smart Environments/Cities, 167-181. Porto, Portugal: Springer International Publishing, 2022.
    10.1007/978-3-030-97516-6_9
  3. Jozi, Aria; Ramos, Daniel; Gomes, Luis; Faria, Pedro; Pinto, Tiago; Vale, Zita. "Demonstration of an Energy Consumption Forecasting System for Energy Management in Buildings". In Progress in Artificial Intelligence, 462-468. Springer International Publishing, 2019.
    10.1007/978-3-030-30241-2_39
Tese / Dissertação
  1. Ramos, Daniel. "Reinforcement Learning of a Multi Agent System for the Forecasting of Electricity Consumption". Mestrado, 2021. https://repositorio-aberto.up.pt/bitstream/10216/138254/2/519034.pdf.
  2. "TensorFlow for automatic prediction of electricity consumption". Licenciatura, 2019.
Atividades

Apresentação oral de trabalho

Título da apresentação Nome do evento
Anfitrião (Local do evento)
2022/04/26 Using diverse sensors in load forecasting in an office building to support energy management in the scope of MAS-SOCIETY GECAD Energy Projects Event 2022
Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento (Porto, Portugal)
2022/04/26 Green Computing: a realistic evaluation of energy consumption for building load forecasting computation in the scope of RETINA project GECAD Energy Projects Event 2022
Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento (GECAD) (Porto, Portugal)
2022/04/01 Energy forecasting models Advanced Training Session in Transactive Energy
RETINA project workshop (Porto, Portugal)
2022/01/12 Reinforcement Learning of a Multi Agent System for the Forecasting of Electricity Consumption Multiagent systems and reinforcement learning in the real world of power systems
Multiagent systems course - FEP (Porto, Portugal)
2021/09/15 Presentation of paper "Using decision tree to select forecasting algorithms in distinct electricity consumption context of an office building" 2021 8th International Conference on Energy and Environment Research
School of Engineering (ISEP) of the Polytechnic of Porto (P.Porto) (Porto, Portugal)
2019/05/23 JOGA&GO app Demo day of LAPASSION project
Instituto Federal de Educação, Ciência e Tecnologia do Maranhão (Porto, Portugal)

Orientação

Título / Tema
Papel desempenhado 		Curso (Tipo)
Instituição / Organização
2021/05/11 - 2021/09/14 Forecast of electric energy consumption in a building
Coorientador
 Project/Internship (PESTA) (Licenciatura/Bacharelato)
Instituto Politécnico do Porto Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento, Portugal

Participação em evento

Descrição da atividade
Tipo de evento 		Nome do evento
Instituição / Organização
2022/04/26 - 2022/04/27 GECAD Energy Projects Event 2022
Oficina (workshop)
 GECAD Energy Projects Event 2022
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2022/04/18 - 2022/04/22 Spring Deep Learn Spring season
Outro
 Spring Deep Learn Spring season
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2022/04/01 - 2022/04/01 RETINA Advanced Training Session in Transactive Energy
Oficina (workshop)
 RETINA Advanced Training Session in Transactive Energy
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2021/07/19 - 2021/07/23 22nd European Agent Systems Summer School
Outro
 22nd European Agent Systems Summer School
Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto, Portugal
2021/06/02 - 2021/06/02 Coordination and Learning in Multiagent Systems: Applications in Robotic Soccer
Outro
 Coordination and Learning in Multiagent Systems: Applications in Robotic Soccer
Universidade do Porto Faculdade de Engenharia, Portugal
2021/05/26 - 2021/05/26 Multi-agent Systems to Distribute Intelligence in Industrial Cyber-Physical Systems
Outro
 Multi-agent Systems to Distribute Intelligence in Industrial Cyber-Physical Systems
Instituto Politécnico de Bragança Centro de Investigação em Digitalização e Robótica Inteligente, Portugal
2020/06/09 - 2020/06/12 Participation in the EEEIC 2020 conference
Conferência
 EEEIC / I&CPS Europe 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe