Joo‐Hyun Song

Papers

Total Citations

H-Index

About

Joo-Hyun Song is a pioneering researcher at the intersection of cognitive neuroscience and human-robot interaction, whose work explores how attention and action shape our perception of space—both our own and that of artificial agents. Her key research areas include the near-hand effect, joint action, and neurobiologically inspired robotics. Song’s major contribution lies in demonstrating that humans prioritize attention to space near a robot’s hand, but only after engaging in collaborative physical interaction—a finding that extends the classic near-hand effect from human dyads to human-robot partnerships. Her 2023 and 2024 papers on iCub’s hand bias (each with 2 citations) reveal that shared action, not mere co-presence, is critical for triggering this attentional shift. In her 2022 neurobiologically inspired robotics model (2 citations), Song dissects the mechanisms of target facilitation and distractor inhibition during goal-directed reaching, offering a computational framework for how selection history biases behavior. Though early in citation impact, her work is notable for bridging embodied cognition and robotics, with implications for designing more intuitive collaborative robots. Song’s research promises to reshape how we understand shared body representations and attention in human-machine teams.