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João A. A. Lopes holds a PhD in Information Systems and Technologies (January 2025) and a Master’s degree in Engineering and Management of Information Systems (August 2020). His academic and research trajectory has been marked by the consolidation of an independent research line in the field of Analytical and Decision Support Systems, with a strong focus on Artificial Intelligence, Machine Learning and Data Engineering, particularly applied to eHealth and Medical Informatics. More recently, his work has expanded towards Generative Artificial Intelligence, with a particular emphasis on Large Language Models (LLMs) and their integration into decision support ecosystems. His research explores the design of intelligent systems capable of combining predictive, prescriptive, and generative capabilities, supporting tasks such as clinical reasoning assistance, automated knowledge extraction, natural language interaction, and cognitive decision support. Since 2019, he has actively collaborated with research groups, progressively strengthening his scientific maturity and autonomy through the design, integration, and validation of adaptive analytical architectures. His work increasingly focuses on AI Systems Architecture, addressing challenges related to the implementation of Adaptive Business Intelligence (ABI) Systems, integration of LLM-based components with Machine Learning, and deployment of scalable, production-ready AI systems in complex environments. In addition, he has devoted particular attention to the operationalization and continuous monitoring of intelligent systems, exploring mechanisms for evaluation, auditing, explainability, and lifecycle management of both predictive and generative AI models. He is currently an Integrated Researcher at Intelligent Data Systems (IDS) Group at the ALGORITMI Research Center and Assistant Professor at the Department of Information Systems, University of Minho, Portugal.
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Identificação

Identificação pessoal

Nome completo
JOÃO ANTÓNIO ARAÚJO LOPES

Nomes de citação

  • LOPES, JOÃO

Identificadores de autor

Ciência ID
5F12-9743-F077
ORCID iD
0000-0001-7854-8293

Endereços de correio eletrónico

  • jlopes@dsi.uminho.pt (Profissional)

Websites

  • https://www.linkedin.com/in/joãolopesit/ (Profissional)

Domínios de atuação

  • Ciências da Engenharia e Tecnologias

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Português (Idioma materno)
Inglês Utilizador proficiente (C1) Utilizador proficiente (C1) Utilizador proficiente (C1) Utilizador proficiente (C1) Utilizador proficiente (C1)
Espanhol; Castelhano Utilizador independente (B1) Utilizador independente (B1) Utilizador independente (B1) Utilizador independente (B1) Utilizador independente (B1)
Formação
Grau Classificação
2020/09/30 - 2025/01/31
Concluído
 Information Systems and Technologies (Doutoramento)
Universidade do Minho, Portugal
"Integrating Artificial Intelligence in Healthcare Organizations: By means of Autonomous Adaptive Business Intelligence" (TESE/DISSERTAÇÃO)
2015/09/15 - 2020/07/31
Concluído
 Management of Information Systems (Mestrado integrado)
Universidade do Minho, Portugal
"Adaptive Business Intelligence: Modelos de Previsão e Otimização na Área da Saúde" (TESE/DISSERTAÇÃO)
Percurso profissional

Docência no Ensino Superior

Categoria Profissional
Instituição de acolhimento 		Empregador
2022 - Atual Professor Auxiliar Convidado (Docente Universitário) Universidade do Minho, Portugal
Universidade do Minho - Departamento de Sistemas de Informação, Portugal

Outros

Categoria Profissional
Instituição de acolhimento 		Empregador
2026/01/01 - Atual Integrated Researcher Researcher Center ALGORITMI, Portugal
2019/07/01 - 2025/12/31 Researcher Researcher Center ALGORITMI, Portugal
Universidade do Minho, Portugal
Projetos

Bolsa

Designação Financiadores
2022/02/01 - Atual Connected Manufacturing - Digital Transformation
UMINHO/BID/2022/10
Investigador
2019/08/28 - 2019/12/31 CIPsi Programmatic Funding
CIPSI-BI-NP-2019-02
Bolseiro de Investigação
Universidade do Minho Centro de Investigação em Psicologia, Portugal
 Fundação para a Ciência e a Tecnologia

Projeto

Designação Financiadores
2020/01/01 - 2024/12/31 Centro de Investigação ALGORITMI
UIDB/00319/2020
10.54499/UIDB/00319/2020
Centro de Computação Gráfica, Portugal

Universidade do Minho, Portugal

Universidade do Minho Centro ALGORITMI, Portugal
Fundação para a Ciência e a Tecnologia
Concluído
2021/06/01 - 2021/11/30 Factory of the Future: Smart Manufacturing
FACTORYOFTHEFUTURE/4_52-02/2021
Bolseiro de Integração na Investigação
BOSCH
Em curso

Outro

Designação Financiadores
2021 - Atual Data Science aplicada à diabetes para aumento de qualidade de vida do doente
01/SAMA2020/2019
Outra
Concluído
2020 - Atual Apoio à Decisão Inteligente na otimização de tempos de resposta e de recursos para melhoria da qualidade de serviço
03/SAMA2020/2019
Outra
Concluído
2025/04/30 - 2026/01/31 INTELLIGENT MODELS FOR OUTPATIENT AND MEDICAL EXAMS SCHEDULING OPTIMIZATION.
2024.07481.IACDC
Researcher
Em curso
2018/12/30 - 2022/12/31 ICDS4IM - Intelligent Clinical Decision Support for Intensive Medicine
DSAIPA/DS/0084/2018
Outra
Concluído
Produções

Publicações

Artigo em conferência
  1. Pereira, J.; Rodrigues, M.; Lobo, A.; Sá, D.; Lopes, J.; Santos, M.F.. "Optimisation Models in Surgical Planning: A Comparative Review". 2025.
    10.1016/j.procs.2025.03.146
  2. Touças, S.; Cruz, D.; Carvalho, M.; Quintas, C.; Lopes, J.; Guimarães, T.; Duarte, J.; Santos, M.F.. "A Predictive Modeling Approach for Estimating Hospital Appointment Duration". 2025.
    10.1016/j.procs.2025.10.251
  3. Amorim, R.; Lobo, A.; Lopes, J.; Guimarães, T.; Duarte, J.; Santos, M.F.. "Comparative Analysis of Optimization Algorithms in Medical Examination Scheduling". 2025.
    10.1016/j.procs.2025.10.250
  4. Cunha, J.; Duarte, R.; Lopes, J.; Guimarães, T.; Santos, M.. "Transforming Healthcare Data: How OpenEHR is Revolutionizing AI-Driven Business Analytics". 2024.
    10.1016/j.procs.2024.11.170
  5. Rodrigues, M.; Pereira, J.; Lobo, A.; Sá, D.; Lopes, J.; Santos, M.. "An Adaptive Business Intelligence Approach to Surgery Scheduling: A Modular Architecture". 2024.
    10.1016/j.procs.2024.11.173
  6. Brito, R.; Lopes, J.; Cerqueira, L.; Barbosa, V.; Matos, C.; Blanco, B.; Guimaraes, T.; Santos, M.F.. "Precision Medicine for Diabetes: Improving the detection of diabetic patients using Predictive Analytics". 2024.
    10.1016/j.procs.2024.06.118
  7. Lopes, T.; Duarte, J.; Cardoso, S.; Miranda, J.; Duarte, R.; Lopes, J.; Santos, M.F.. "Classification Models for Early Prediction of Surgical Site Infections". 2024.
    10.1016/j.procs.2024.06.114
  8. Lobo, A.; Barbosa, A.; Guimarães, T.; Lopes, J.; Peixoto, H.; Santos, M.F.. "Better Medical Efficiency by Means of Hospital Bed Management Optimization—A Comparison of Artificial Intelligence Techniques". 2023.
    10.1007/978-3-031-49011-8_21
  9. Gomes, J.; Lopes, J.; Guimaraes, T.; Santos, M.F.. "Identifying Diabetic Patient Profile Through Machine Learning-Based Clustering Analysis". 2023.
    10.1016/j.procs.2023.03.116
  10. Carpinteiro, C.; Lopes, J.; Abelha, A.; Santos, M.F.. "A Comparative Study of Classification Algorithms for Early Detection of Diabetes". 2023.
    10.1016/j.procs.2023.03.117
  11. LOPES, JOÃO; Braga, João; Fernandes, Isabel; Santos, Manuel Filipe. "Applying optimization models in the scheduling of medical exams". Trabalho apresentado em The International Conference on Emerging Data and Industry 4.0 (EDI40), 2022.
  12. Vaz, Maria João; LOPES, JOÃO; Braga, João; Santos, Manuel Filipe. "Intelligent support for diabetic patient treatment planning". Trabalho apresentado em The International Conference on Emerging Data and Industry 4.0 (EDI40), 2022.
  13. Fernandes, I.; Lopes, J.; Braga, J.; Santos, M.F.. "Applying optimization models in the scheduling of medical exams". 2022.
    10.1016/j.procs.2022.03.093
  14. Vaz, M.J.; Lopes, J.; Peixoto, H.; Santos, M.F.. "Predictive Analytics to support diabetic patient detection". 2022.
    10.1016/j.procs.2022.03.092
  15. LOPES, JOÃO; Braga, João; Santos, Manuel Filipe. "An ABI platform and its contributions as a support in the evolution to Hospital 4.0". Trabalho apresentado em The International Conference on Emerging Data and Industry 4.0 (EDI40), 2021.
    Publicado
  16. Sousa, Ana; LOPES, JOÃO; Santos, Manuel Filipe. "mHealth: Monitoring Platform for Diabetes Patients". Trabalho apresentado em The International Conference on Emerging Data and Industry 4.0 (EDI40), 2021.
    Publicado
  17. Lopes, J.; Braga, J.; Santos, M.F.. "Adaptive business intelligence platform and its contribution as a support in the evolution of hospital 4.0". 2021.
    10.1016/j.procs.2021.04.016
  18. Sousa, A.L.; Lopes, J.; Guimarães, T.; Santos, M.F.. "MHealth: Monitoring platform for diabetes patients". 2021.
    10.1016/j.procs.2021.03.113
  19. LOPES, JOÃO; Guimarães, Tiago; Santos, Manuel Filipe. "Adaptive Business Intelligence: A New Architectural Approach". Trabalho apresentado em The International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH), 2020.
    Publicado
  20. LOPES, JOÃO; Guimarães, Tiago; Santos, Manuel Filipe. "Predictive and Prescriptive Analytics in Healthcare: A Survey". Trabalho apresentado em The International Conference on Emerging Data and Industry 4.0 (EDI40), 2020.
    Publicado
  21. Lopes, J.; Guimarães, T.; Santos, M.F.. "Adaptive business intelligence: A new architectural approach". 2020.
    10.1016/j.procs.2020.10.075
  22. Lopes, J.; Guimarães, T.; Santos, M.F.. "Predictive and Prescriptive Analytics in Healthcare: A Survey". 2020.
    10.1016/j.procs.2020.03.078
Artigo em revista
  1. João Lopes; Marcelo Dionisio; Mariana Faria; Manuel Filipe Santos. "Exploring trends and autonomy levels of adaptive business intelligence in healthcare: A systematic review". PLOS ONE (2024): https://doi.org/10.1371/journal.pone.0302697.
    10.1371/journal.pone.0302697
  2. João Lopes Sr; Tiago Guimarães; Júlio Duarte; Manuel Santos. "Enhancing Surgery Scheduling with Artificial Intelligence: A Study on Metaheuristic Optimisation Models in Healthcare Settings (Preprint)". JMIR Medical Informatics (2024): https://doi.org/10.2196/57231.
    10.2196/57231
  3. Rui Macedo; Agostinho Barbosa; João Lopes; Manuel Santos. "Intelligent Decision Support in Beds Management and Hospital Planning". Procedia Computer Science 210 (2022): 260-264. http://dx.doi.org/10.1016/j.procs.2022.10.147.
    10.1016/j.procs.2022.10.147
  4. Mariana Faria; Agostinho Barbosa; Tiago Guimarães; João Lopes; Manuel Santos; Diogo Peixoto; Hugo Peixoto. "Predictive analytics for hospital discharge flow determination". Procedia Computer Science 210 (2022): 248-253. http://dx.doi.org/10.1016/j.procs.2022.10.145.
    10.1016/j.procs.2022.10.145
Capítulo de livro
  1. Lara Ferreira; João Lopes; Júlio Duarte; Daniela Ferreira; Rogério Pires; Isabel Silva; Manuel Santos. "Time Series Modeling for Smart Energy Consumption in Industry 4.0". 2026.
    10.1007/978-3-032-05176-9_18
  2. Ricardo Duarte; João Cunha; João Lopes; Francini Hak; Tiago Guimarães; Manuel Filipe Santos. "Blockchain Analytics in Healthcare: Leveraging Open Data Standards and Adaptive Business Intelligence for Trustworthy Decision Making". 2025.
    10.1007/978-3-031-94950-0_16
  3. Ricardo Duarte; João Lopes; Tiago Guimarães; Susana Ferreira; Manuel Filipe Santos. "Business Intelligence Platform for COVID-19 Monitoring: A Case Study". 2023.
    10.1007/978-3-031-38204-8_4
  4. Diogo Peixoto; Mariana Faria; Rui Macedo; Hugo Peixoto; João Lopes; Agostinho Barbosa; Tiago Guimarães; Manuel Filipe Santos. "Determining Internal Medicine Length of Stay by Means of Predictive Analytics". 171-182. Springer International Publishing, 2022.
    10.1007/978-3-031-16474-3_15
  5. ?ngela Alpoim; João Lopes; Tiago A. Guimar?es; Portela, Filipe; Manuel F. Santos. "A Framework to Evaluate Big Data Fabric Tools". Estados Unidos, 2020.
    10.4018/978-1-7998-5781-5.ch009
  6. Alpoim, Â.; Lopes, J.; Guimarães, T.; Portela, C.F.; Santos, M.F.. "A framework to evaluate big data fabric tools". 180-191. 2020.
Pré-impressão
  1. João Lopes Sr; Tiago Guimarães; Júlio Duarte; Manuel Santos. "AI-based Metaheuristic Optimization Models for Surgery Scheduling Problems in Healthcare (Preprint)". 2024. https://doi.org/10.2196/preprints.57231.
    10.2196/preprints.57231