Jihye Song

University of Central Florida

Papers

2

Total Citations

23

H-Index

2

About

Jihye Song is a leading researcher in human-robot interaction (HRI), with a focus on how social cognition shapes our encounters with autonomous machines. Her work bridges robotics and cognitive science, exploring how subtle social cues—such as a robot’s display and proxemics behavior—influence human responses during dynamic tasks like hallway navigation. In her most-cited study (14 citations), she demonstrated that varying a robot’s social signals significantly alters participants’ social reactions, laying groundwork for designing more intuitive robotic companions. Expanding on this, her 2019 paper (9 citations) broke new ground by linking individual differences in theory of mind—the ability to attribute mental states to others—to how people perceive a robot’s intentions and emotions. This work reveals that our capacity to “read the mind” of a robot is not uniform, but deeply personal. Song’s contributions are vital for creating socially aware robots that adapt to diverse human users, and her findings have implications for assistive technology, autonomous vehicles, and collaborative robotics. Her research is widely cited in HRI and cognitive science communities, marking her as a rising voice in understanding the psychology of human-machine interaction.

Research Focus

Key Achievements

2
H-Index
2
Papers
23
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Effects of Social Cues on Social Signals in Human-Robot Interaction During a Hallway Navigation Task
14 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Central Florida

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago