Heereen Shim

Korea Institute of Industrial Technology

Papers

Total Citations

H-Index

About

Heereen Shim’s research focuses on the intersection of virtual reality (VR), deep learning, and human-robot interaction, with a particular emphasis on enhancing teleoperation and collaborative robotics. Their most cited work, "Development of VR visualization system including deep learning architecture for improving teleoperability" (2017, 4 citations), introduces a novel system that integrates deep learning to recognize and visualize remote environments in both 2D and 3D, enabling tele-operators to work more effectively and safely. This contribution addresses critical challenges in remote control by providing real-time, intuitive situational awareness. In a related study, "Object-Human Interaction Pattern Generating System using Deep Learning" (2017, 2 citations), Shim explores human activity recognition to enable robots to anticipate and collaborate with humans in industrial and service settings. Though early in their career, these works lay foundational groundwork for smarter, more adaptive robotic systems. Shim’s research is particularly relevant to advancing human-robot teamwork, where deep learning-driven perception and VR interfaces bridge the gap between human intent and machine action. Their work signals a promising trajectory in making teleoperation and human-robot collaboration more seamless and intuitive.