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Maicon Herverton Lino Ferreira da Silva Barros

Universidade de Pernambuco, Campus Surubim · Universidade de Pernambuco

https://researchid.co/maiconherverton
@upe.br
133Google Scholar Citations
6Google Scholar h-index
3Google Scholar i10-index

Biography

Professor at Universidade de Pernambuco (UPE), Campus Surubim (2025-). Postdoctoral researcher (UnB, 2025–). Postdoctoral researcher (UPE, 2024–2025) and Ph.D. in Computer Engineering from the Graduate Program of the Polytechnic School of Pernambuco, at the University of Pernambuco (PPGEC – POLI – UPE, 2024). Holds a Master’s degree in Applied Informatics (UFRPE, 2013) and a Bachelor’s degree in Information Systems (UFRPE, 2011). Member of the dotLAB Brazil research group in partnership with Dublin City University (DCU). Scientific reviewer for Frontiers (1664-3224), Heliyon (Elsevier, 2405-8440), iScience (Elsevier, 2589-0042), and Latin American Data in Science (LADS, 2763-9290). Associate member of the IEEE Bahia Section (#94484272). Former recipient of scholarships from PFA/UPE Quality Program (2021), FACEPE/UPE Technical Productivity Grant BCT-1768-1.03/21 (2022), and BCT-0778-1.03/22 (2023).

Education

Postdoctoral researcher (UPE, 2024–2025) and Ph.D. in Computer Engineering from the Graduate Program of the Polytechnic School of Pernambuco, at the University of Pernambuco (PPGEC – POLI – UPE, 2024). Holds a Master’s degree in Applied Informatics (UFRPE, 2013) and a Bachelor’s degree in Information Systems (UFRPE, 2011).

Recent Google Scholar Publications

  1. On the usage of artificial intelligence for identifying main attributes and predicting neonatal sepsis
    Scientific Reports , 2026, 2026
  2. Machine Learning Classification of Favorable vs Unfavorable Tuberculosis Treatment Outcomes Using Clinical and Sociodemographic Data from Brazil’s SINAN-TB (2001–2023)
    2025
  3. On Usage of Artificial Intelligence for Predicting Neonatal Diseases, Conditions and Mortality: A Bibliometric Review
    IEEE Access , 2025, 2025 | Citations: 1.0
  4. Leveraging AI and Data Visualization for Enhanced Policy-Making: Aligning Research Initiatives with Sustainable Development Goals
    Sustainability 16 (24), 11050 , 2024, 2024 | Citations: 2.0
  5. UTILIZAÇÃO DE INTELIGÊNCIA ARTIFICIAL PARA A PREDIÇÃO DE MORTALIDADE NEONATAL EM PERNAMBUCO
    II SIMPÓSIO DE NEONATOLOGIA DA UNIVERSIDADE DE PERNAMBUCO , 2024, 2024

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