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About

Monica Reggiani is a prominent robotics researcher whose work spans autonomous robot control, human-robot interaction, rehabilitation robotics, and wearable sensing technologies. Over two decades, she has made substantial contributions to how robots are programmed, controlled, and integrated into real-world applications. Among her most influential contributions is her pioneering work on programming by demonstration (PbD) in virtual environments, where she explored intuitive methods for users without technical expertise to teach robots complex assembly tasks — work that accumulated over 88 citations and helped shape accessible robot programming paradigms. Her research on real-time control systems addressed the critical challenge of task overload in autonomous robots, proposing rate modulation strategies that remain foundational in the field. Reggiani has also made meaningful strides in rehabilitation robotics, notably applying Support Vector Machine classifiers to electromyographic signals for locomotion intention detection, advancing human-robot interfaces for patient rehabilitation. Her later work on wearable inertial sensors and model-based inverse kinematics further demonstrates her commitment to practical human motion estimation. With a cumulative citation count exceeding 400 across her most recognized papers, Reggiani's interdisciplinary expertise — bridging software architectures, motion planning, and biomedical sensing — has established her as a versatile and enduring voice in robotics research.