Minyu Yang
Papers
1
Total Citations
6
H-Index
1
About
Minyu Yang is a pioneering researcher at the intersection of robotics, deep learning, and medical imaging, with a primary focus on robot-assisted sonography. Their most impactful work introduces a unified deep imitation learning and control framework that enables robots to perform complex ultrasound scanning—a task traditionally requiring significant human dexterity and real-time image interpretation. By integrating motion control with force regulation guided by live ultrasound feedback, Yang’s framework allows robotic systems to learn from expert demonstrations and adapt to patient responses, effectively bridging the gap between autonomous manipulation and clinical practice. Although early in its trajectory, this 2023 publication has already garnered 6 citations, signaling strong interest from both the robotics and medical communities. Yang’s contributions are particularly notable for addressing a critical bottleneck in healthcare automation: the safe, adaptive, and precise execution of contact-rich procedures. Their work holds promise for expanding access to diagnostic ultrasound in underserved settings and reducing clinician workload. As a rising voice in embodied AI for medicine, Minyu Yang is shaping the future of intelligent, assistive robotics in clinical environments.
Research Focus
Key Achievements
Top Papers
- 1