I am a researcher at the Centre Borelli since March 2020, working on machine learning for time series analysis. I focus a large part of my research activity on the problem of change point detection in multivariate signals. Various settings are considered: supervised as well as unsupervised, classical statistical models and end-to-end training deep signal representations. In addition to studying the theoretical aspects of those methods, I put much effort into proposing documented and efficient implementations (mostly in Python and C/C++). I also work on graphs/networks, in particular graph signal processing for various applications.
From an application standpoint, I mainly manipulate medical data, taken from a wide range of clinical protocols that are developed in the Centre Borelli. Recently, industrial and financial data tend to occupy a larger part of my focus. Whenever possible, I try to share the data I work on with the research community.