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About

Giulia Cisotto is a leading researcher at the intersection of neural engineering and human-machine interaction, whose work is reshaping rehabilitation for stroke survivors. Her primary research areas span brain-computer interfaces (BCIs), neurorehabilitation, and intelligent robotic systems. Cisotto’s most significant contribution is pioneering BCI-based motor rehabilitation for stroke patients, particularly through her development of closed-loop, sensorimotor training paradigms that integrate contingent force feedback to promote neuroplasticity and functional recovery. Her seminal 2011 review, *Brain-Computer Interface in Stroke: A Progress Report*, has garnered 221 citations, establishing a foundational framework for the field. She has also demonstrated the clinical translation of her work with a proof-of-principle brain-machine interface for upper limb training, and a platform that enhances arm reaching ability in chronic stroke patients. Beyond neural interfaces, Cisotto has innovated in low-cost, inkjet-printed sEMG electrode matrices for gesture recognition, and applied game theory to multi-agent robotic area survey. Her research not only advances fundamental understanding of brain-machine interaction but also delivers tangible, low-cost tools for clinical and assistive technologies, making her a pivotal figure in modern neurorehabilitation.