We work on the the development of reliable machine learning techniques that can be safely in high risk domains such as healthcare. Although the research questions we try to answer coming from healthcare applications, the methods we develop are generic and transversal making them relevant to application domains sharing the same difficulties. Some current and previous research projects are showcased below:

Anomaly Detection

Learning-based methods for anomaly detection in different applications

Health Monitoring

                Wearable devides and smart city sensors data for healthcare monitoring

ML Fundamentals

Efficient techniques to optimize the learning process of ML-based systems