In this thesis we investigate the properties of the Wavelet Scattering Transform (WST), a mathematical technique recently proposed in the context of signal processing and ML. We explore the application of WST in distinguishing glitches that impact the accurate detection of gravitational waves (GW). This thesis is done in collaboration with the Istituto Nazionale di Fisica Nucleare (INFN), in the interTwin project framework. This work investigates the possibility of applying WST to extract discriminative features from glitches, i.e. noises captured by gravitational wave detectors not related to astrophysical phoenomena. Physical issues, e.g. non-homogeneity in centering the time-series over the energy spike, environmental noise and deformations caused by the high sensitivity of the interferometer are problems that critically plague the state-of-the-art techniques.