English 
Italiano 
Bayesian inference proves to be a robust tool for the fitting of parametric models on experimental datasets. In the case of electron kinetics, it can help the identification of non-thermal components in electron population and their relation with plasma parameters and dynamics. We present here a tool for electron distribution reconstruction based on MCMC (Monte Carlo Markov Chain) based Bayesian inference on Thomson Scattering data, discussing the computational performances of different algorithms and information metrics. Along, a possible integration between Soft X-ray spectroscopy and Thomson Scattering is presented, focusing on the parametric optimization of diagnostics spectral channels in different plasma regimes.
In a world increasingly facing new challenges at the forefront of plasma scientific research and technological innovation, CNR and ISTP pledge progress and achieve an impact in the integration of research into societal practices and policy
