Samaneh Manavi Roodsari

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About

Samaneh Manavi Roodsari is a leading researcher at the intersection of optical fiber sensing and deep learning, with a primary focus on advancing continuum robotics for minimally invasive surgery. Her key research areas include shape sensing using fiber Bragg gratings (FBGs), machine learning for sensor modeling, and medical robotics. Dr. Roodsari’s major contributions lie in developing novel deep-learning approaches to achieve precise, real-time 3D shape estimation of snake-like continuum manipulators—critical for improving surgical navigation and control. Her pioneering work, such as "Shape sensing of optical fiber Bragg gratings based on deep learning" (2023, 14 citations), demonstrates how supervised learning can overcome the limitations of traditional FBG shape reconstruction, offering enhanced accuracy and robustness. In her earlier feasibility study (2021, 6 citations), she established the foundational framework for using deep neural networks to model edge-FBG sensors, addressing key challenges like electromagnetic noise immunity and miniaturization. These innovations have significant implications for robot-assisted surgeries, enabling safer and more precise interventions. Dr. Roodsari’s work is highly regarded for bridging optical physics with artificial intelligence, making her a notable figure in the growing field of intelligent medical devices.