Jeesoo Ha

Seoul National University, Korea Advanced Institute of Science and Technology

Papers

Total Citations

105

H-Index

About

Jeesoo Ha is a pioneering researcher at the intersection of soft robotics, computer vision, and human-robot interaction. Her work focuses on developing intuitive, intelligent control systems for wearable and teleoperated robots, with a particular emphasis on making robotic assistance more responsive to human intent. Ha’s most significant contribution is her 2019 paper "Eyes are faster than hands," which introduced a novel learning-based methodology that uses egocentric (first-person) camera views to predict user intentions for soft wearable robots. This approach, which has garnered 91 citations, bypasses traditional, slower control methods by allowing the robot to "see" what the user intends to do, dramatically improving reaction time and natural interaction. She has also advanced the field through deep learning for position estimation and control of soft gloves (2018), addressing the complex modeling challenges inherent in deformable materials. Additionally, her work on virtual reality mapping systems for mobile robot teleoperation (2018) enhances operator immersion by effectively visualizing sensor data. Ha’s research is notable for its practical, user-centric approach, bridging the gap between complex robotic systems and seamless, intuitive human control.