Jiahe Pan

Papers

Total Citations

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About

Jiahe Pan is an emerging researcher specializing in human-robot interaction, shared control systems, and teleoperation. Their work sits at the intersection of robotics, cognitive science, and human factors engineering, addressing one of the field's most pressing challenges: how to optimally balance human and robot capabilities in collaborative tasks. Pan's research makes meaningful contributions to understanding how shared control frameworks influence operator cognitive load, trust, and overall task performance in teleoperated systems. Their application of Fitts' Law as a benchmarking tool for assisted human-robot performance represents a novel methodological approach, offering the field a principled framework for evaluating how robotic assistance should dynamically adapt to varying task demands. This work is particularly relevant for deploying robots in hazardous or high-stakes environments where human operators face significant cognitive burdens. Though early in their career, with their most-cited works each accumulating 2 citations since 2024–2025, Pan is contributing to a rapidly growing research area with broad implications for healthcare robotics, remote surgery, and industrial automation. Their focus on the relationship between adaptive assistance and cognitive workload positions them as a promising voice in the next generation of human-robot collaboration research.