Max Robotics — Global Service Robot Directory + US Certification

About

Meenakshi Narayan’s research lies at the intersection of medical robotics, data-driven safety systems, and engineering education. Her primary contributions focus on enhancing the reliability of robotic needle steering—a technique used to navigate flexible needles around obstacles to reach deep tissue targets. She pioneered data-driven methods to detect critical adverse events such as needle buckling, tissue displacement, and undesired curvature changes during insertion, using axial force and sensor data to prevent placement errors. Her work on a compact force forecasting technique enables early prediction of safety-critical events, improving robot-environment interaction in medical applications. With over 20 citations across her most-cited papers, Narayan’s impact is evident in advancing safer, more autonomous surgical robots. Notably, she has also contributed to reshaping engineering education by fostering critical thinking through open-ended problems in the era of generative AI, addressing academic integrity challenges. Additionally, her exploration of photoluminescence-based needle tip tracking offers a novel, all-optical alternative for minimally invasive surgery, promising enhanced patient safety. Through her innovative, interdisciplinary approach, Narayan continues to push boundaries in both robotic surgery and pedagogical reform.