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About

Masoud Shafiee is a robotics researcher whose work bridges the gap between theoretical control systems and practical robotic applications, particularly in legged locomotion and medical rehabilitation. His research focuses on nonlinear robust control, adaptive estimation, and the emerging field of cognitive robotics. Shafiee’s early contributions include developing a nonlinear robust controller for a 5-link biped robot during the double support phase (2010, 9 citations), as well as modeling and iterative learning control for quadruped robots (2011, 5 citations). He has also advanced human-robot interaction by proposing an adaptive estimation mechanism for robot-environment forces when interacting with soft tissues (2015, 7 citations). More recently, Shafiee has pioneered the use of fractional order systems and biological signals—including EEG processing—for optimal control of robotic hands in rehabilitation (2022, 2024, each with 3 citations). His work on singular system theory for quadruped walking robots (2013, 3 citations) further demonstrates his versatility in mathematical modeling. With a career spanning over a decade, Shafiee’s research is increasingly relevant to assistive robotics and neurorehabilitation, making him a notable figure in the integration of control theory with biomedical engineering.