Zahra Shahrbaf is a Doctoral Candidate in Rehabilitation Robotics at Tyromotion within the MSCA DN–AERIALIST project. Her research focuses on in-game assessment and adaptive robotic assistance in unsupervised home rehabilitation, aiming to create engaging and personalized therapeutic experiences. She integrates machine learning, control systems, and human-centered design to extract patient-specific performance metrics for smarter robotic behavior and progressive difficulty adjustment.

Zahra earned her Master’s in Electrical Engineering – Control Systems from Isfahan University of Technology. Her previous work includes AI-based emotion detection in educational robots, image-based defect detection in industrial robotics, and data-driven user behavior analysis for energy optimization.

Her research interests include adaptive control, reinforcement learning, robotics, and intelligent data fusion for personalized rehabilitation.