Lyes Kadem

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About

Lyes Kadem is a leading researcher at the intersection of robotics, artificial intelligence, and medical imaging, with a primary focus on advancing cardiac ultrasound technology. His work centers on developing intelligent robotic systems for autonomous cardiac examinations, where he has made pioneering contributions to force control and visual servoing. In his highly cited 2024 paper, Kadem introduced an AI-powered robust interaction force control method for cardiac ultrasound robotic systems, employing dual control loops and AI-driven image feedback to simultaneously enhance image quality and patient safety. This work has garnered 10 citations for its novel approach to balancing clinical precision with patient comfort. Building on this foundation, his 2025 paper presents a robust deep feature ultrasound image-based visual servoing technique, featuring the development of UCF-Net—a specialized convolutional neural network trained in a supervised manner to enable automatic cardiac examination. With 5 citations, this work demonstrates Kadem’s ability to translate complex AI architectures into practical clinical tools. His research is notable for its direct impact on improving diagnostic accuracy and procedural safety in cardiology, positioning him as a key innovator in medical robotics.