Jerald Yoo

National University of Singapore, Seoul National University

Papers

Total Citations

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About

Jerald Yoo is a leading innovator at the intersection of integrated circuits and robotic perception, pioneering ultrasound-based vision systems that overcome the fundamental limitations of traditional cameras. His research focuses on developing custom ASICs for all-weather, low-power 3D sensing, enabling machines to "see" in conditions where cameras fail—such as fog, darkness, or rain. Yoo’s major contribution is the introduction of a Universal Energy Recycling TX (UERTX) architecture, which dramatically reduces power consumption in ultrasound transceivers. His 2022 work on an ultrasound ASIC for metamorphic robotic vision demonstrated a >7-meter range with only 4.3 mW per channel, achieving a compact, lightweight system (100g, 5×5×5 cm³) suitable for drones and robots. This work has garnered over 9 citations and represents a paradigm shift from conventional CMOS image sensors, which lack depth sensing and struggle in adverse conditions. Yoo’s systems integrate 64-channel TX/RX paths for real-time 3D navigation, offering a robust alternative to LiDAR and radar. His 2024 study on real-time ultrasound imaging for UAVs further cements his role in advancing non-visual robotic perception, making him a key figure in the future of autonomous systems.