My current research focuses on the development of machine learning techniques that can be safely deployed in high risk domains, such as healthcare, by addressing data complexity, low tolerance to errors and poor reproducibility.
My research agenda is structured around three axis:
- Interactive machine learning for data handling
- Error assessment to assist high-risk decisions
- Definition and setup of evaluation and validation frameworks.
- 01-09-2021: Paper accepted at the M2Ms-2 Challenge within STACOM 2021
- 31-08-2021: Outstanding reviewer award for ICCV 2021
- 20-07-2021: One paper accepted at ECML-PKDD Workshop on Advanced Analytics and Learning on Temporal Data
- 16-07-2021: Our paper on learning-based EEG wearable design has been accepted at IEEE EMBC
- 24-05-2021: I have been awarded a Junior chair at the 3IA Institute Côte d'Azur