Machine Learning for Bioinformatics and Personalised Medicine

The research focus of the group is on advancing machine learning methodologies to support translational research and to inform clinical decision-making.
By integrating different sources of data with prior knowledge and leveraging cutting-edge machine learning techniques, such as causal reasoning, physics-informed modelling and federated learning, our research aims to contribute to the understanding of complex biological systems and to the improvement of healthcare outcomes.