Projects
Computational Neuroscience
Development of computational approaches to understand neural systems, at micro- and macro-scale level.
- Higher-order topological approaches of brain connectivity
- Structure-function approaches to analyze fMRI data
- Machine learning approaches to neuroimaging data in healthy and clinical population
Time Series Analysis
Methods to analyze multivariate signals
- Forecasting methods for complex time series
- Higher-order inference in temporal data
- Arrow of time in time-varying signals
Multilayer Networks
Investigation of multilayer network structures and their applications in understanding complex interconnected systems.
- Complexity and reducibility of multiplex networks
- Models and measures for multiplex networks
- Strategies of optimal percolation for multiplex networks