Uran Oh

Ewha Womans University, University of Maryland, College Park

Papers

Total Citations

H-Index

About

Uran Oh is a researcher whose work bridges haptic interaction, robotics, and cognitive systems. Her key research areas include encountered-type haptic rendering, texture synthesis, and metacognitive robotics. Oh’s major contribution lies in advancing haptic feedback for virtual and augmented reality. In her most cited work, "Synthesizing the Roughness of Textured Surfaces for an Encountered-Type Haptic Display Using Spatiotemporal Encoding" (2020, 9 citations), she proposed a novel method to simulate realistic texture sensations without complex tactile actuators—a significant step toward making haptic displays more practical and immersive. This work addresses a core challenge in encountered-type haptic rendering: providing free-to-touch, move-and-collide sensations that feel authentic. Beyond haptics, Oh has explored metacognition in robotics, co-authoring visionary papers such as "The robot baby and massive metacognition: Future vision" (2012, 9 citations) and "The robot baby and massive metacognition: Early steps via growing neural gas" (2012, 8 citations). These works envision robots that learn like infants, using metacognition to synergize machine learning and commonsense reasoning. Her interdisciplinary approach—combining tactile engineering with cognitive robotics—positions her as a forward-thinking researcher shaping how machines perceive and interact with the physical world.