Maryam Zekri
Papers
5
Total Citations
165
H-Index
5
About
Maryam Zekri is a leading researcher in intelligent robotic control, specializing in adaptive impedance control and neural-network-based systems for robotic manipulators operating in unknown and varying environments. Her work focuses on enabling robots to dynamically adjust their stiffness and force in real time—critical for applications from manufacturing to surgical robotics. Zekri’s most influential paper, “Intelligent Impedance Control using Wavelet Neural Network for dynamic contact force tracking in unknown varying environments” (2021, 71 citations), introduces a wavelet neural network framework that allows robots to maintain precise force control without prior knowledge of the environment. She further advanced this with recurrent fuzzy wavelet neural networks and dynamic surface techniques, addressing challenges like actuator saturation and friction uncertainties. Her research on the da Vinci surgical robot (2019) demonstrates practical impact, modeling complex friction dynamics to improve precision in minimally invasive surgery. With over 165 total citations, Zekri’s contributions are foundational for next-generation adaptive robotic systems that must interact safely and effectively with unpredictable surroundings. Her work is essential reading for engineers developing intelligent, force-sensitive robots for healthcare, industry, and beyond.
Research Focus
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