Artificial Intelligence and Machine Learning

The objective of this research area is to develop applications of machine learning and artificial intelligence techniques to problems in the areas of production engineering, logistics, transportation and health.

In particular, the OPL laboratory has developed projects applying the techniques of reinforcement learning, Bayesian models, Kalman filters and artificial neural networks.

This project has the support of NVidia , by means of its GPU Academic Grant Program.

This project studies the modeling of stochastic sequential decision problems that occur in the areas of production, logistics, and transportation. The problems are addressed using approximate dynamic programming techniques and reinforcement learning. This project is funded by the Universal CNPq 2021 call for proposals and is also supported by NVidia, through its academic GPU donation program.

Currently, Prof. Anselmo R. Pitombeira Neto is part of the research team of the AI4Wellness project, funded by Samsung and executed by InsightLab, a laboratory linked to the UFC's Computer Science Department. The goal of the AI4Wellness project is to develop machine learning models using Samsung smartwatch data with applications in health and wellbeing.