Rudy MOREL

In Medecine, Physics, Econometrics, we possess data observed along time. We can think of the recordings of the simultaneous activity of several brain area. This data can be studied along two axes. First, along time, we observe causality phenomena which are the trace of the course of time from past to future. Secondly, we observe dependencies between several series at fixed time, indicating that several parts of the brain communicates at certain time.

The goal is to model these multiple time series being as close as possible to the observation. We use approaches from Data Science called unsupervised which adapts well to several domains.