Max Robotics — Global Service Robot Directory + US Certification

About

Dasha Shieff is a researcher at the forefront of human-robot interaction, specializing in electromyography (EMG)-based control systems for robotic telemanipulation. Her work focuses on developing intuitive muscle-machine interfaces (MuMIs) that allow users to control robotic and prosthetic devices naturally through their own muscular signals. Shieff’s major contributions include pioneering shared control frameworks that combine EMG-based motion estimation with compliance control, enabling safer and more intuitive operation of robots in remote or hazardous environments. Her most cited paper (2022, 25 citations) comprehensively assesses machine learning techniques and feature extraction methods for dexterous robotic telemanipulation, while her 2021 work (19 citations) systematically compares ML approaches for decoding human intention from myoelectric signals. Shieff’s research addresses the critical challenge of creating embodied, hands-free control systems for applications ranging from prosthetics to search and rescue operations. Her pilot studies on shared control frameworks (18 and 5 citations) demonstrate how combining human muscular activations with autonomous compliance can simplify complex telemanipulation tasks. Through her innovative integration of machine learning, signal processing, and control theory, Shieff is advancing the next generation of intuitive, wearable interfaces that bridge human intention with robotic action.