Yuki Funayama

Papers

Total Citations

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About

Yuki Funayama is a robotics and automation researcher whose work bridges human-robot interaction and industrial inspection. His key research areas include teleoperation systems, deep learning for visual recognition, and autonomous plant monitoring. Funayama’s major contribution is the development of a dual-arm robot teleoperation framework enhanced by a virtual world model, which allows operators to intuitively control complex robotic tasks with improved precision and safety—a critical advancement for hazardous environments. This work, published in 2020, has garnered 9 citations, reflecting its growing relevance in teleoperation research. In parallel, Funayama pioneered an automatic analog meter reading system using deep neural networks for plant inspection, achieving robust performance in real-world industrial settings (5 citations). This innovation reduces human error and labor in routine monitoring tasks. His research demonstrates a practical focus on deploying AI and robotics to solve tangible industrial challenges, with potential applications in manufacturing, energy, and disaster response. Funayama’s work is notable for its integration of virtual and physical systems, offering a scalable path toward safer, more efficient automation.