Papers
8
Total Citations
181
H-Index
7
About
Young-Guk Ha is a pioneering researcher in ubiquitous robotics and artificial intelligence, best known for conceptualizing the Ubiquitous Robotic Companion (URC)—a vision of networked service robots that seamlessly integrate with ambient sensors and devices to provide on-demand assistance anytime, anywhere. His foundational work on the Ubiquitous Robotic Service Framework (2005, 52 citations) and service-oriented integration using Semantic Web technologies (2005, 41 citations) established key architectural principles for connecting robots with ubiquitous computing environments. Ha’s design of a “ubiquitous robotic space,” comprising physical, semantic, and virtual layers, has been widely cited (25+ citations) and remains influential in ambient intelligence and robot service frameworks. More recently, his research has expanded into deep learning for autonomous driving, including hybrid neural networks for driving scene understanding and generative adversarial networks (L-GAN) for privacy-preserving face de-identification. With over 180 total citations across his most-cited works, Ha’s contributions bridge early ubiquitous robot middleware with modern AI-driven perception, making him a notable figure in the evolution of intelligent, context-aware robotic systems.
Research Focus
Key Achievements
Top Papers
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- 4Design and Implementation of a Ubiquitous Robotic Space25 citations · 2009
- 5Driving Scene Understanding Using Hybrid Deep Neural Network9 citations · 2019
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- 8Efficient Driving Scene Image Creation Using Deep Neural Network5 citations · 2019