Josh Bhagat Smith

Ames Research Center, Oregon State University

Papers

Total Citations

H-Index

About

Josh Bhagat Smith’s research lies at the intersection of virtual reality, surgical simulation, and human-robot teaming, with a focus on enhancing training, teleoperation, and collaborative transparency. His most cited work, “Virtual reality extensions into surgical training and teleoperation” (2003, 5 citations), pioneered the integration of immersive VR with robotics for astronaut training and remote surgical assistance, laying groundwork for realistic, usable simulations that improve preparation and assessment in high-stakes environments. Building on this, his 2024 paper “Improving Human-Robot Team Transparency with Eye-tracking based Situation Awareness Assessment” (2 citations) introduces a novel ocular metric to gauge situation awareness in human-machine teams. By leveraging eye-tracking data, Smith’s approach enables real-time assessment of transparency, fostering more effective collaboration between humans and autonomous systems. This work is particularly notable for its potential to enhance decision-making in fields like space exploration and surgery, where shared understanding is critical. Though his citation counts are modest, Smith’s contributions are foundational—bridging VR, robotics, and cognitive metrics—and his eye-tracking methodology offers a fresh, practical tool for advancing human-robot interaction. His research continues to inspire new directions in transparent, adaptive teaming.