Artificial intelligence, language processing, and data science

Scope

This line investigates how artificial intelligence techniques, especially machine learning, language models, and data science, can organize, retrieve, and interpret large volumes of textual, scientific, and institutional information. It includes literature-review support platforms, repository mining, predictive models, and decision-support systems for public agencies.

Results materialize in products such as Contextus and Evidentia and in projects with partners such as IBICT, MCTI, and INPI. CEDIS is part of UnB’s Integrated Research Center in Artificial Intelligence (CenIA).

Research questions

• How can language models support systematic reviews and the curation of scientific evidence?
• Which data representations make technical information retrieval more accurate and explainable?
• How can machine learning and data science be integrated into public institutions' workflows safely and transparently?

Main methods

• Experiments with machine learning models
• Evaluation of information retrieval systems
• Prototyping with partners
• Institutional data analysis

Recent output 66

1. 2026 ·Software/patent registration
   Computer program registration certificate: Contextus
   Sergio Antônio Andrade de Freitas, André Corrêa da Silva, Milena de Faria Silva, Renan Carneiro Batista
2. 2026 ·Software/patent registration
   Computer program registration certificate: Chatbot as a Support Tool for Requirements Engineering
   Fause Carlos Mascarenhas Lustosa Junior, George Marsicano Corrêa, Pedro Henrique Muniz de Oliveira
3. 2026 ·Software/patent registration
   Computer program registration certificate: Chatbot for Administrative Inquiries at FCTE/UnB
   Breno Henrique de Souza, George Marsicano Corrêa, Giulia Domingues de Alcantara
4. 2026 ·Software/patent registration
   Computer program registration certificate: Machine Learning Application for Non-Invasive Prediction of Euploidy in Human Embryos
   George Marsicano Corrêa, Maria Eduarda dos Santos Abritta Ferreira, Sabrina Caldas Berno
5. 2026 ·Undergraduate thesis
   EstocAI: intelligent inventory manager
   Luis Eduardo Carneiro Miranda, Vinícius Mendes Martins
6. 2026 ·Conference paper
   A Heterogeneous Ensemble Meta-Model for Large-Scale Categorization of Portuguese Scientific Records in OasisBR
   Sergio Antônio Andrade de Freitas, André Corrêa da Silva, Milena de Faria Silva, Renan Carneiro Batista, Washington Luís …
7. 2026 ·Conference paper
   Fast University Timetabling via Room-wise CP-SAT Decomposition and Incremental Repair
   Éber Júnio Borges Moreira, Sergio Antônio Andrade de Freitas
8. 2026 ·Conference paper
   A Motivation-Aware Diagnostic Instrument for Personalized and Gamified Computing Education
   Sergio Antônio Andrade de Freitas, Daniel Rodrigues da Rocha, Davi Rodrigues da Rocha, Mylena Angélica Silva Farias

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Linked supervisions 36

1. 2026 · TCC1 (proposal)
   AI applied to Software Engineering: An analysis of the transformations caused by AI in Software Engineering development activities
   Ian Lucca Soares Mesquita, Christian Hirsch Santos
2. 2026 · TCC1 (proposal)
   Intrusion Detection System with Machine Learning
   Henrique Azevedo Batalha, Marina Márcia Costa de Souza
3. 2026 · TCC1 (proposal)
   Gamification and Large Language Models: Development of an Educational Platform
   Israel Thalles Dutra dos Santos
4. 2026 · Undergraduate thesis
   EstocAI: intelligent inventory manager
   Luis Eduardo Carneiro Miranda, Vinícius Mendes Martins
5. 2025 · Master's dissertation
   Automated identification of elementary processes through HTTP request analysis
   Diego Emanuel Ferreira da Rocha
6. 2025 · Undergraduate thesis
   Three Filters: analyzer of scientific information
   Leonardo Milomes Vitoriano, Mateus de Almeida Dias

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