Athyrson M. Ribeiro – Marcos M. Raimundo

Institute of Computing - University of Campinas

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Athyrson M. Ribeiro is a Ph.D. candidate in Computer Science at the Institute of Computing at the University of Campinas (IC - UNICAMP). He is a member of the Recod.ai lab. He is also a member of the Hub of Artificial Intelligence and Cognitive Architectures (HIAAC), performing research in Trusthyworth AI, mainly in the area of reject inference and explainability.

Interests

Credit Scoring
Reject Inference
Data Science
Ethical AI

Education

PhD in Computer Science, 2028 Institute of Computing - University of Campinas

MS in Computer Science, 2024 Institute of Computing - University of Campinas

BSc in Computer Science, 2019 State University of Piauí

Publications

Balancing Performance and Inclusion: A Novel Reject Inference Framework for Credit Scoring

Athyrson Machado Ribeiro, Marcos M Raimundo (2026). The 2nd Workshop on Advances in Financial AI Workshop: Towards Agentic and Responsible Systems.

Balancing Performance and Reject Inclusion: A Novel Confident Inlier Extrapolation Framework for Credit Scoring

Athyrson Machado Ribeiro, Marcos Medeiros Raimundo (2025). arXiv preprint arXiv:2510.12967.

Best practices for responsible machine learning in credit scoring

Giovani Valdrighi, Athyrson M. Ribeiro, Jansen SB Pereira, Vitoria Guardieiro, Arthur Hendricks, Décio Miranda Filho, Juan David Nieto Garcia, Felipe F. Bocca, Thalita B. Veronese, Lucas Wanner, Marcos Medeiros Raimundo (2025). Neural Computing and Applications.

Um estudo comparativo entre cinco métodos de otimização aplicados em uma rnc voltada ao diagnóstico do glaucoma

Athyrson Machado Ribeiro (2020). Revista de Sistemas e Computação-RSC.

Rede inception v3 voltada a identificaçao do glaucoma: Comparaçao entre métodos de otimizaçao

Athyrson M Ribeiro, S Francisco de Paula (2019). Escola Regional de Computação Aplicada à Saúde (ERCAS).

Projects

AI for Finance - HIAAC

The goal of this research line is to develop robust and transparent AI models for credit analysis and similar problems in the financial sector, such as fraud detection.