The main objective of the Data Science Axis is to bring together researchers from the 5 teams of LIPN working in areas related to data science by creating forums, workshops, and scientific exchange days within LIPN. It targets researchers developing innovative methods as well as those wishing to apply approaches around a common theme, that of analysing and extracting rich information from potentially massive, heterogeneous, distributed, imperfect, structured raw data. With diverse application domains including health, education, automotive, and more.
This axis will also address essential and powerful models enabling a detailed analysis of the characteristics and structure of data. At the heart of this approach are several key elements such as machine learning, knowledge representation, natural language processing, Combinatorial Optimisation, logic models, formal verification.
Keywords: machine learning, natural language processing, generative models, optimisation, logic, verification.