The primary objective of the Data Science axis is to bring together researchers from all five LIPN teams working in data science-related fields. It aims to facilitate forums, workshops, and scientific exchange days within the laboratory, while strengthening collaborations between researchers in these areas.
The axis targets both researchers developing innovative methods and those seeking to apply approaches centered around a common theme: analyzing and extracting rich information from raw data that may be massive, heterogeneous, distributed, imperfect, and/or structured. These methods are applied across various fields such as healthcare, education, and the automotive industry.
This research axis also addresses essential and powerful models for the fine-grained analysis of data characteristics and structure. At the heart of this approach lies the study, development, and application of key methods from machine learning, knowledge management, natural language processing, reasoning, optimization, and logic.