Fariba Khosravian

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About

Fariba Khosravian is a researcher whose work sits at the intersection of human-robot interaction, surgical robotics, and skill transfer. Her primary research focuses on developing learning-based frameworks that enable robots to guide and augment human performance in high-stakes medical procedures. In her most cited work, "Towards Skill Transfer via Learning-Based Guidance in Human-Robot Interaction: An Application to Orthopaedic Surgical Drilling Skill" (2019, 20 citations), she introduced a novel approach for transferring expert surgical skills to novices through interactive robotic guidance. This contribution is particularly significant for orthopaedic training, where precision drilling is critical. By combining machine learning with haptic feedback, Khosravian’s work addresses a key challenge in surgical education: how to effectively and safely teach complex motor skills. Her research has implications for reducing surgical errors and improving patient outcomes. With 20 citations, this paper has already established her as a promising voice in the field, and her ongoing work continues to push the boundaries of how robots can serve as collaborative partners in skill acquisition.