Biography:
Dante Trabassi is a Research Fellow at Sapienza University of Rome working in movement disorders and artificial intelligence. His research focuses on wearable sensor–based gait analysis, explainable machine learning, and digital biomarkers in Parkinson’s disease and rare neurodegenerative conditions. He develops interpretable AI frameworks integrating biomechanics, entropy-based metrics, and generative modelling for early disease stratification and risk prediction. His work has been published in peer-reviewed journals and presented at international conferences in neurology, artificial intelligence and biomedical engineering.
Title : From gait features to latent instability: A Bayesian threshold framework for fall occurrence in Parkinson’s disease
Title : Explainable wearable gait biomarkers identify high prodromal burden in Parkinson’s disease