The research at the Siena Artificial Intelligence Laboratory (SAILab) is focused on machine learning methods and their applications. In particular, the theoretical topics concern: the study of models and algorithms for learning in structured domains, with emphasis on their computational power and complexity (Graph Neural Networks); the development of hybrid statistical-neural models; the techniques related to the idea of learning from constraints, with specific focus on models able to combine learning from examples with a knowledge base of logic rules expressed by First Order Logic; models able to learn online from streams of data, such as learning visual features from videos or knowledge extraction from text streams.
Application fields of interest are bioinformatics and medical data analysis, text mining, natural language processing and conversational agents, information extraction and retrieval, computer vision, and speech recognition.
ERC Keywords PE6_10 Web and information systems, database systems, information retrieval and digital libraries, data fusion PE6_11 Machine learnig, statistical data processing and application using signal processing (e.g. speech, image, video) PE6_13 Bioinformatics, biocomputing, and DNA and molecular computation PE6_7 Artificial intelligence, intelligent systems, multi agent systems PE6_9 Human computer interaction and interface, visualization and natural language processing