Ung Hee Lee
Papers
3
Total Citations
79
H-Index
3
About
Ung Hee Lee is a leading researcher at the intersection of electric motor design and intelligent robotic control, with a focus on creating high-performance, lightweight systems for autonomous and wearable applications. Lee’s work is defined by two major contributions: the empirical characterization of exterior-rotor brushless DC (BLDC) motors and the development of novel control strategies for wearable robots. In a highly cited 2019 study (46 citations), Lee provided a foundational empirical model for high-torque-density BLDC motors, critical for drones and humanoid robots. Building on this, a 2020 paper (30 citations) introduced a groundbreaking strategy using image transformation and convolutional neural networks to encode human locomotor intent, enabling more intuitive control of autonomous wearable robots. Lee’s most recent work (2023) offers a practical framework for modeling BLDC motors in lightweight robotic systems, bridging the gap between theoretical design and real-world application. With a growing citation impact, Lee is recognized for advancing both the hardware and software that power next-generation robotics, from aerial vehicles to assistive exoskeletons.
Research Focus
Key Achievements
Top Papers
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