Pushing the frontiers of artificial intelligence, computer vision, machine learning and data science — from theory to real-world application.
Excellence in AI and intelligent systems research, with publications in prestigious international conferences and journals.
CSI Lab is the Intelligent Systems Computing Laboratory at the Federal University of Ouro Preto (UFOP), affiliated with the Department of Computer Science (DECOM/ICEB).
Our mission is to advance artificial intelligence, machine learning, computer vision, pattern recognition and data science — combining academic excellence with practical applications of social and industrial impact.
We develop models and systems applied to healthcare, finance, environment and language — with publications in Springer, IEEE, SBC and ScienceDirect.
We collaborate with companies such as EFI Bank, CGU, Embrapii and BDMG on R&D projects, transferring knowledge to society.
From deep learning to biometric recognition — our research groups cover the main frontiers of intelligent computing.
AI models applied to high-complexity problems in healthcare, finance, language and environmental perception.
Visual pattern recognition, image classification, deepfake detection and biometric identification.
Deep neural networks, transfer learning, self-supervised learning and efficient architectures (NAS).
Language models for Portuguese, toxic text classification, speech recognition and prompt optimization.
Credit risk analysis, fraud detection, churn prediction and epidemiological time series.
Spatial cluster detection, COVID-19 modeling with GNN and urban mobility, epidemiological surveillance.
ECG classification, arrhythmia detection, heartbeat segmentation and remote cardiac signals via video (rPPG).
Evolutionary algorithms, community detection in social networks and Pareto solution dispersion/concentration optimization.
Our projects stem from real-world questions and produce results published in the top international venues — IEEE, Springer, SBC — along with open-source code available to the community via GitHub.
Applied research projects with industrial and government partners.
Questions about applications, research and partnerships with the lab.
Follow the lab's achievements, conference participations and awards.
IX Regional School of Computing Applied to Health — best paper award given to a work advised by Prof. Eduardo Luz.
Exact Sciences category — best undergraduate research work at UFOP, recognizing machine learning research.
Source code for all published papers available at github.com/ufopcsilab.