Jonghong Kim

Papers

Total Citations

H-Index

About

Jonghong Kim is a researcher whose work lies at the intersection of cognitive robotics and human-robot interaction, with a particular focus on enabling machines to understand and anticipate human behavior. His most cited paper, "Human-Robot Interaction using Intention Recognition" (2015), explores how robots can infer human intentions by learning affordances—the actionable possibilities that objects and environments offer an agent. This foundational contribution addresses a critical challenge in robotics: moving beyond pre-programmed responses toward adaptive, context-aware interaction. By modeling the relationship between an agent, its environment, and potential actions, Kim’s research helps robots respond more naturally and proactively to human needs. While his citation count is modest, his work on intention recognition and affordance learning represents a meaningful step toward more intuitive and collaborative robotic systems. For students and researchers entering the field of human-robot interaction, Kim’s research offers a clear and practical entry point into understanding how robots can become more perceptive partners in shared tasks.