Our Machine Learning work advances generalisation, interpretability, and fairness. We develop methods for limited labels, distribution shifts, and hybrid symbolic-statistical reasoning, with applications in health diagnostics, industrial monitoring, and intelligent decision support.
People in ML
3 researchers contribute to this area across LIACC units.
Selected projects
CRAI — Center for Responsible AI
Meta-learning and data generation to build robust algorithm cards that evaluate models against responsible-AI principles.
RETAILL
Software combining environmental, territorial and supply-chain data into actionable information for optimised, lower-waste food logistics.
Sono ao Volante 2.0
An information system to predict drowsiness at the wheel and detect chronic sleep disturbance or deprivation.
QVida+
An information system for continuous monitoring of the quality of life of oncology patients.