Graduated in Information Systems from the Federal Rural University of Rio de Janeiro in 2018, holds a Master's degree
in Computer Science from the Federal University of Rio de Janeiro, obtained in 2022.
Currently, a Ph.D. student, conducting a research funded by the AON Foundation focused on assessing the economic losses
caused by natural disasters on resilience, utilizing artificial intelligence. He is a member of the TECNUN Resilience Group and the World
Alliance on Digitalization for Disaster & Emergency Management (WADDEM). He has also worked as a researcher with
the Knowledge Engineering Group (GRECO) and the Virus Outbreak Data Network Brazil (VODAN-BR). His research
interests include data science, machine learning, FAIR principles, resilience, disaster losses and climate change.
Publications
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GAP: Enhancing Semantic Interoperability of Genomic Datasets and Provenance Through Nanopublications
Matheus Pedra Puime Feijoó, Rodrigo Jardim, Sergio Manuel Serra da Cruz & Maria Luiza Machado Campos
Published in: Metadata and Semantic Research, 2022
Access paper here
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Improving the Traceability of (Meta)data Through Semantically Enriched Nanopublications.
Matheus Pedra Puime Feijoó, Rodrigo Jardim, Sergio Manuel Serra da Cruz & Maria Luiza Machado Campos
Published in: T7 Workshop of Provenance Week, 2021
Access paper here
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Evaluating FAIRness of Genomic Databases
Matheus Pedra Puime Feijoó, Rodrigo Jardim, Sergio Manuel Serra da Cruz & Maria Luiza Machado Campos
Published in: Advances in Conceptual Modeling, 2020
Access paper here
Professional experience
GRECO
Research for possible solutions to enhance semantic interoperability and data provenance in scientific repositories,
taking the genomic area as a use case. This investigation bases on FAIR data principles, nanopublication and FAIR
Knowlet schema
VODAN-BR
Participate in developing and providing an infrastructure to enable healthcare facilities to collect and implement
patient data management that carries SARS-CoV2, the new Coronavirus, ensuring the confidentiality and privacy of
patient data, following the FAIR data principles.
Course instructor, Teaching assistant and Academic advisor
Develop and taught lessons relate to data science.
Additionaly, mentored groups to the database, computer and society, and bioinformatic subjects.
Further, mentor undergraduate students in their undergraduate thesis projects related to Bioinformatics,
Nanopublication and SDGs topics.