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About

Suhun Jung is a robotics researcher whose work bridges the critical gap between human biomechanics and autonomous robotic control. His primary research areas include bipedal locomotion, rehabilitation robotics, and human-robot interaction. Jung’s most influential contribution is his work on standing balance control for bipedal robots, where he applied behavior cloning to enable stable physical interaction with environments—a fundamental challenge in humanoid robotics (8 citations). In rehabilitation, he developed a novel robotic system with a muscle-to-muscle interface that provides stage-appropriate physical exercise and muscular stimulation for post-stroke patients (5 citations), and created a gait rehabilitation system capable of assisting pelvic movement during normal walking, addressing the limitation of sagittal-plane-only training (4 citations). Demonstrating the versatility of his expertise, Jung also contributed to pandemic response by designing a deep neural network-based visual feedback system for teleoperated nasopharyngeal swab sampling, reducing healthcare workers’ infection risk (3 citations). His work uniquely combines machine learning, biomechanics, and clinical application, making tangible impacts on both autonomous robotics and patient care.