Haralambos Dafas
Papers
2
Total Citations
4
H-Index
1
About
Haralambos Dafas is an emerging researcher working at the intersection of human-robot interaction, computer vision, and pose estimation. His work focuses on enabling robots to better perceive, understand, and interact with humans in social and physical spaces — a critical challenge as robots become increasingly integrated into everyday environments. Dafas's most notable contribution to date is the HARPER dataset, introduced in 2024, which represents a significant step forward in 3D human body pose estimation and forecasting. What distinguishes HARPER from prior datasets is its emphasis on the robot's own perspective — leveraging onboard sensors from Boston Dynamics' quadruped robot, Spot — to capture dyadic human-robot interactions in realistic conditions. This work has already attracted early citations, reflecting the research community's interest in robot-centric perceptual frameworks. Complementing this, his research into quadruped robot gait perception investigates how a robot's movement style shapes human social responses — a relatively unexplored but practically important question for designing socially acceptable robots. Though still in the early stages of building his citation record, Dafas is addressing timely and meaningful problems in embodied AI and social robotics, positioning himself as a contributor to watch in this rapidly evolving field.
Research Focus
Key Achievements
Top Papers
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