Data Science and Complex Systems
The aim of the ‘Data Science and Complex Systems’ theme is to develop and promote models, methods and software in the field of information science. Situated at the intersection of the fields of computer science, automatic control, signal processing and mathematics, it considers several scientific issues linked to digital technology: BigData, robotics, control and supervision of large systems, human-machine interaction, intelligent embedded systems, etc.
Information sciences are a cross-disciplinary key today, and Centrale Lille’s teams are targeting the following major societal challenges: Information and communication society (cyber-physical systems / IoT, optimisation and processing of large masses of data, information security), Climate change & Bio-economy (data processing for catalysis, active control of microbiota, coastal water monitoring), Clean, safe and efficient energy (stability and supervision of smart electricity grids), Green and integrated intelligent transport (active aerodynamics for vehicles of the future, autonomous vehicles, energy consumption of rolling stock), Mobility and sustainable urban systems (optimisation and multimodality), Life, Health and Wellbeing (flexible robotics for surgery, wearable sensors, models for neuroscience).
This work is part of the three hubs of the I-SITE ULNE (Université Lille Nord-Europe): mainly ‘Human-Friendly Digital World’, but also ‘Science for a Changing Planet’ and ‘Precision Human Health’.
The research activities in this area contribute to both data science and complex systems science. The research development strategy is to combine a strong theoretical component with applications that have a recognised socio-economic impact.
To carry out this research, Centrale Lille relies on its seven teams at the Lille Centre for Research in Computer Science, Signal Processing and Automation (CRIStAL), including three joint project teams with INRIA.