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About

Maide Bucolo is a researcher whose work sits at the compelling intersection of robotics, human-machine interaction, and biomedical engineering. Her most significant contributions center on teleoperated medical robotics, particularly remote ultrasound scanning systems, where she has advanced the integration of force-feedback control to enhance precision and usability in remote clinical procedures. Her 2020 paper on force feedback assistance in remote ultrasound scans has garnered 19 citations, while her 2022 comprehensive review of teleoperated medical robots — timely in its attention to COVID-19-driven shifts in healthcare — has accumulated 16 citations, together establishing her as a notable voice in medical robotics research. Beyond medical applications, Bucolo has explored Brain-Computer Interface (BCI) systems, investigating how neural signals can be translated into commands for controlling external devices, with meaningful implications for individuals with motor disabilities. Her earlier work in bio-inspired locomotion control using Cellular Neural Networks further demonstrates the breadth of her engineering vision. More recently, she has turned to machine learning approaches for classifying motor imagery EEG signals, reflecting her ongoing commitment to intelligent, adaptive human-machine systems. Across more than two decades, Bucolo's research consistently bridges engineering innovation with real-world human benefit.