Based in Campus Biotech, the Data science team is specialized in information processing. Advanced information processing is a major area of development in the group and is achieved thanks to state-of-the-art data representation, interpretation, and storage. Expert in three pillars of artificial intelligence: knowledge processing, symbolic approaches, and approaches based on machine learning, the group also disposes of unique resources and skills in the field of natural language processing in the domains of health and medicine in the French language. The research in the Data science team is divided into three hubs: 

Knowledge engineering

To process data efficiently, a strategy regarding knowledge building and handling is needed. Each project needs and creates knowledge. Therefore we need to store and access this new knowledge as well as linking it in a coherent network of meaning. This strategy revolves around three axes: knowledge management, conceptual representation, and lexico-semantic resources. more info

Symbolic reasoning

One of the two main branches of Artificial Intelligence (AI) resides in symbolic knowledge-driven approaches. Symbolic AI systems represent language phenomena via logical rules. Such rules are highlighted via multiple tasks such as: lexical analysis, pattern matching, and knowledge representation and reasoning. more info

Machine learning

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. As part of the group’s techniques are: automatic classification, word embeddings, and information retrieval. more info