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About

Subin Joo is a robotics researcher whose work bridges the gap between intelligent control systems and assistive technology, with a primary focus on robotic prosthetic hands and precision medical robotics. His most impactful contribution lies in developing deep learning-based object detection frameworks that enable robotic prosthetic hands to autonomously select appropriate grasping patterns and control strategies based on visual input. This work, detailed in his 2022 paper "Grasping Time and Pose Selection for Robotic Prosthetic Hand Control Using Deep Learning Based Object Detection," has garnered 9 citations and represents a significant step toward restoring intuitive, natural hand function for amputees. Building on earlier foundational research from 2020, Joo’s approach allows prosthetic devices to interpret their environment and execute context-aware grasps without requiring explicit user commands. More recently, Joo has extended his expertise to medical robotics, designing a novel system that combines a Stewart platform with a remote center of motion (RCM) mechanism for non-invasive brain stimulation. This 2025 work addresses critical limitations in conventional serial-link robots, offering enhanced precision and inherent safety constraints. By integrating computer vision, deep learning, and advanced mechanical design, Subin Joo is advancing both rehabilitation robotics and neurosurgical assistance, demonstrating a clear trajectory from fundamental control systems to clinically relevant applications.