Foto do Prof. José M Parente de Oliveira

Prof. José M Parente de Oliveira

Full Professor | Computer Science Department

Aeronautics Institute of Technology (ITA)

About me

I am a Full Professor at the Computer Sceince Department of the Aeronautics Institute of Technology. I hold a Doctorate in Electronic Engineering and Computing from the Aeronautics Institute of Technology (ITA - Instituto Tecnológico de Aeronáutica). I coordinated the Big Data Science Laboratory and the Complementary Training Program in Data Science at ITA, served as the Head of the Computer Science Department at ITA until March 2020, and I am a collaborating researcher at The National Center for Ontological Research (NCOR) at the State University of New York at Buffalo.

My research interests include Computer Science, Ontology, Knowledge Graphs, Linked Data/Semantic Web, and Neuro-Symbolic AI (knowledge representation and LLMs). I am the director of the Data & Ontology Research Group

http://dgp.cnpq.br/dgp/espelhogrupo/731693

in which we carry out reserach and development projects.

Research Interests

Computer Science

The foundational study of computation, information, and automation, encompassing everything from theoretical algorithms to software engineering and the development of intelligent systems.

Ontology

A branch of knowledge representation that defines a formal set of concepts, categories, and properties within a specific domain to establish a shared, machine-readable vocabulary for data and relationships.

Knowledge Graphs

Large-scale networks of interconnected entities and their relationships, organized into a graph structure that enables complex querying and provides a structured "backbone" for AI systems to understand real-world context.

Linked Data / Semantic Web

An extension of the World Wide Web that uses standardized protocols (like RDF and SPARQL) to interlink diverse datasets across the internet, transforming the web into a global, machine-readable database.

Neuro-Symbolic AI

A hybrid AI paradigm that combines the pattern-recognition strengths of Neural Networks (like LLMs) with the logical reasoning and explicit knowledge representation of Symbolic AI, aiming to create models that are both powerful and explainable.

Some Selected Publications

Using Process Mining Techniques to Enhance the Patient Journey in an Oncology Clinic
SANTOS, RICARDO S.; BRAZ, JAQUELINE B.; CAPELLI, MICHELLE; RODRIGUES, ALVARO O. I.; PRENTE DE OLIVEIRA, JOSÉ M.
Informatics-Basel, v. 13, p. 28, 2026.
📄 PDF | 🔗 https://www.mdpi.com/2227-9709/13/2/28
A Semantic Model to Describe RESTful Services
RODRIGUEZ, LUÍS ANTONIO DE ALMEIDA; PARENTE DE OLIVEIRA, JOSÉ M.
IEEE Access, v. 1, p. 1-1, 2025
📄 PDF | 🔗 http://dx.doi.org/10.1109/ACCESS.2025.3562503
An Ontology of Tobacco Production: Enriching Large Language Model-based Decision Support
ALVES, L. F. M.; Parente de Oliveira, José M; BONACIN, R.; ROSA, F. F.
RITA, v. 32, p. 102-111, 2025.
📄 PDF | 🔗 http://dx.doi.org/10.22456/2175-2745.146658
Influencing Factors on Internal Auditing Maturity Using PLS-PM
DE LANNES MAIA, RICARDO VALERIO; BRIGIDO, WILLIAMSON JOHNNY H.; DE OLIVEIRA, JOSE M PARENTE
IEEE Access, v. 1, p. 1-1, 2024.
📄 PDF | 🔗 http://dx.doi.org/10.1109/ACCESS.2024.3442160
A RDF-based Graph to Representing and Searching Parts of Legal Documents
OLIVERIA, F.; Parente de Oliveira, José M
Artificial Intelligence and Law, v. 1, p. 667-695, 2023.
📄 PDF | 🔗 http://dx.doi.org/10.1007/s10506-023-09364-9
Formal Verification With Frama-C: A Case Study in the Space Software Domain
OLIVERIA, F.; Parente de Oliveira, José M
IEEE Transactions on Reliability, v. 65, p. 1163-1179, 2016
📄 PDF | 🔗 http://dx.doi.org/10.1109/tr.2015.2508559
Concept maps as the first step in an ontology construction method
PARENTE DE OLIVEIRA, J. M.; STAR, R. R.
Information Systems (Oxford), v. 1, p. 771-783, 2013.
📄 PDF | 🔗http://dx.doi.org/10.1016/j.is.2012.05.010
Towards Defining Computer Capability
PARENTE DE OLIVEIRA, J. M.
The Joint Ontology Workshops - FOUST VII: 7th Workshop on Foundational Ontology, 2023, Sherbrooke, Québec, Canada. Proceedings of the Joint Ontology Workshops 2023. Episode IX: The Quebec Summer of Ontology, co-located with the 13th International Conference on Formal Ontology in Information Systems (FOIS 2023), 2023. v. 3637
📄 PDF | https://ceur-ws.org/Vol-3637

Para lista completa de publicações, consulte meu perfil no https://lattes.cnpq.br/9413052240755786

Recent Courses

Database Techniques (Técnicas de Banco de Dados)

Code: CSI-30

The course objective is to provide a theoretical and practical foundation on the main database techniques, including the various methods of data storage, retrieval, and analysis. Syllabus: Systems Development Concepts. Database Concepts. Conceptual Model. Entity-Relationship Model (ERM). Relational Model. Storage Structures. Structured Query Language (SQL). Query Processing. Relational Algebra and Calculus. Transaction and Concurrency. Data Warehouse. Data Mining. Big Data Techniques. Relational Database Design.

Undergrad Course

Ontology and Data Modeling

Code: CE-266

There is a consensus nowadays that the WWW has profound impact on the way people communicate with each other, how information is disseminated and accessed, and how business is carried out. Along with the internet, information systems generate tons of data every day. As a consequence, information systems need more powerful ways to cope with such a data deluge in terms of organizing, retrieving and processing data according to the business in question. This course is all about the technologies, languages and tools related to the use of ontologies in data modeling to support information systems, such as technical and administrative applications database, and AI applications. Syllabus: General Concepts of Data. Conceptual Modeling. General Concepts and Types of Ontologies. Foundational Ontologies. Ontology Development. Ontology Implementation with OWL. Knowledge Graphs. Relational Data Modeling. Non Relational Data Modeling. Ontology-Based Data Integration. Ontology Roles in Information and Artificial Intelligence Systems. Ontology and Knowledge Graph in LLM.

Grad Course

Supervisees/ Advisees With Defined Project

Post-doc

Ferrucio de Franco Rosa ((Start date: 2025)
Modelagem Conceitual para Resposta a Incidentes de Segurança Cibernética

Doctorate

Antonio Gilberto de Moura (Start date: 2025)
Application of Ontologies and Natural Language Processing in the Identification of Repetitive Lawsuits as Candidates for the Incident of Resolution of Repetitive Demands (IRDR)
Aplicação de ontologias e processamento de linguagem natural na identificação de demandas judiciais repetitivas candidatas à aplicação do Incidente de Resolução de Demandas Repetitivas (IRDR)
Williamson Johnny Hatzinakis Brigido (Start date: 2023)
THE EFFECTS OF DIFFERENT FACTORS ON GDP, ENVIRONMENT AND SOCIAL ASPECTS IN BRAZILIAN STATES - A DATA SCIENCE APPROACH

Master's

Antonio Gustavo Silveira Dantas (Start date: 2024)
Study of a Knowledge Graph Model for Restricting LLM Analysis Context
Estudo de Modelo de Grafo de Conhecimento para Restringir Contexto de Análise de LLM
Douglas Silva Teixeira (Start date: 2025)
Graphs as a Foundation for System Integration Architecture and Artificial Intelligence
Grafos como base para Arquitetura de Integração de Sistemas e Inteligência Artificial
Erika Kurauchi (Start date: 2024)
Which contextual factors influence the adoption of cloud computing in organizations, and how can these decisions be supported?
Quais fatores contextuais influenciam a adoção da computação em nuvem nas organizações e como essas decisões podem ser apoiadas?
Henrique Madruga Tavares (Start date: 2024)
A situation analysys model for enhancing situational awareness through situation calculus for border monitoring

Research Initiation

Maria Antonia Correa Picanco Del Nero Gomes (Scholarship ITAEx/NUBANK)
Study of LLM powered by knowledge graph
Estudo de LLM alimentada com grafo de conhecimento

Contact

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Office

Electronics and Computing Building, Room 111
Aeronautics Institute of Technology (ITA)
Pca Mal do Ar Eduardo Gomes, 50, CEP 12.228-900

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Phone

+55 (12) 3947-6941