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About

Uksang Yoo is a pioneering researcher at the intersection of soft robotics, proprioceptive sensing, and human-robot interaction. His work centers on enabling soft pneumatic robots to perceive their own shape and environment—a fundamental challenge due to their infinite degrees of freedom and complex deformations. Yoo’s most impactful contribution is his 2023 paper on zero-shot sim-to-real transfer learning for 3D proprioceptive sensing in pneumatic soft robots (12 citations), which demonstrates how simulation-trained models can directly control real-world soft robots without retraining. He also developed the Deterministically Adjusted Stiffness-Pneumatic Elastomer Robot (DAS-PER), an analytical design methodology that allows soft robots to display preprogrammed elongation and bending with tunable stiffness (8 citations). In 2024, Yoo introduced POE, an acoustic soft robotic proprioception system for omnidirectional end-effectors, and MOE-Hair, a soft, compliant robot for contact-rich hair manipulation and care—addressing labor shortages in elderly care. His recent work, PneuGelSight (2025), fuses vision-based proprioception with tactile sensing, while SonicBoom uses microphone arrays for contact localization in visually occluded environments. With over 40 citations across his publications, Yoo is establishing himself as a leading voice in making soft robots safer, smarter, and more capable in unstructured, human-centric settings.