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About

Tengyue Wang is a rising researcher at the intersection of mixed reality (MR), medical robotics, and human-robot collaboration. Their work focuses on enhancing surgical precision and safety through immersive technologies and intelligent shared control. Wang’s most cited paper, “MR Meets Robotics: A Review of Mixed Reality Technology in Robotics” (2022, 8 citations), provides a foundational survey of MR applications in robotics, addressing a critical gap in the literature. In “Dynamic Virtual Fixture Generation Based on Intra-Operative 3D Image Feedback in Robot-Assisted Minimally Invasive Thoracic Surgery” (2024, 4 citations), Wang introduced a novel method for generating real-time virtual fixtures from 3D imaging, enabling seamless shared control in dynamic surgical environments. Their work on “Immersive Human-Robot Interaction for Dexterous Manipulation in Minimally Invasive Procedures” (2022, 4 citations) further advances computer-assisted surgery by integrating immersive interfaces with robotic manipulators. Additionally, Wang’s “Virtual Potential Field-Based Motion Planning for Human-Robot Collaboration via Kinesthetically Guided Teleoperation” (2023, 3 citations) proposes a kinesthetic guidance strategy that improves collaborative teleoperation. With a clear trajectory toward safer, more intuitive surgical robotics, Wang’s contributions are shaping the future of MR-enhanced medical interventions.