Papers
5
Total Citations
55
H-Index
3
About
Yaesol Kim is a pioneering researcher at the intersection of haptic interaction and robotic task planning, whose work is redefining how humans physically engage with virtual and remote environments. Her primary contributions lie in encountered-type haptics (ETH), a paradigm that allows users to touch and feel virtual objects without wearing cumbersome actuators. Kim’s landmark paper, “Encountered‐type haptic display for large VR environment using per‐plane reachability maps” (2018, 36 citations), introduced the H-Wall system—a seven-degree-of-freedom manipulator that renders realistic wall and door sensations in large-scale VR, establishing a foundation for unencumbered haptic feedback. She further advanced the field by synthesizing surface roughness through spatiotemporal encoding (2020, 9 citations), enabling texture perception without tactile actuators. Expanding ETH’s utility, Kim’s 2023 work (4 citations) applied it to immersive bilateral teleoperation, allowing intuitive bare-hand interaction for remote tasks. Recently, she has ventured into neuro-symbolic AI, co-authoring “Fast and Accurate Task Planning using Neuro-Symbolic Language Models and Multi-Level Goal Decomposition” (2024–2025, 6 citations combined), which merges LLMs with symbolic planners to solve long-sequential robotic tasks efficiently. With a growing citation impact and a knack for bridging hardware and software, Kim is shaping the future of embodied interaction and autonomous robotics.
Research Focus
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Top Papers
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