Machine-Learning methodologies for multimodal data fusion and analysis

The research programme aims to develop innovative methodologies for multimodal data analysis and data fusion based on machine learning techniques. The objective is to design architectures capable of processing and correlating information from heterogeneous sources, ensuring reliability and adaptability in real-world and dynamic contexts, with a view to developing monitoring systems for anomaly prediction and detection in edge environments.