SD - Data science

It brings together researchers in Grenoble working in statistics, machine learning, signal and image processing, and is open to collaborations with all scientific fields in which data analysis plays a key role.

Two main complementary directions are envisaged for PERSYVAL-3: methodological developments and issues related to climate change and the energy crisis (in connection with the Sustainability axis of PERSYVAL-3). In particular, the SD axis is interested in (but not limited to) the following methodological issues:

• Multimodality, large scale, big data,
• Causal inference,
• Private data in data science,
• Selective inference, conformal inference,
• Bayesian approaches,
• Resilient data science (robustness, low-tech).

The two main fields of application are data science for climate science and the design of low-tech procedures (low consumption, low memory, etc.).

Research area coordinators:

Florent Chatelain (Gipsa-lab), Stéphane Girard (LJK)