Giulia Masi

Giulia Masi is a Ph.D. candidate in Computer and Systems Engineering at Politecnico di Torino, Department of Control and Computer Science (DAUIN), specializing in data science, computer vision, and AI applications for Parkinson’s disease rehabilitation and remote monitoring. She also serves as an external lecturer and teaching assistant, contributing to Computer Science courses in the Aerospace Engineering program.

• University: Politecnico di Torino
• Department: Control and Computer Science (DAUIN)
• Academic Rank: Lecturer

Her research integrates life sciences and technology, focusing on neurodegenerative diseases like Parkinson’s. She employs neurophysiological signals, biosignal processing, and serious games to study emotional and motor symptoms, aiming to reduce clinicians' workload through automation.

Giulia’s recent publications highlight trends in RGB-D sensor validation, deep learning for hand tracking, and semi-supervised approaches for Parkinson’s assessment. These works span conferences like IEEE EMBC and journals such as Electronics and Artificial Intelligence in Medicine, emphasizing clinical AI and remote monitoring.

She is a member of the SMILIES research group, which focuses on resilient computer architectures and life sciences collaborations. Her educational background includes a Master’s in Biomedical Engineering at Politecnico di Torino (2021), where her thesis automated REM sleep without atonia scoring—a critical task for early Parkinson’s detection. Prior to her Ph.D., she worked as a research fellow in the Neuroscience Department at the University of Turin, analyzing neurophysiological signals for quantitative symptom measurements.