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About

Hanying Liang is an emerging researcher at the intersection of medical robotics, autonomous imaging systems, and intelligent control, with a focus on advancing minimally invasive and diagnostic procedures through cutting-edge automation. His most notable contributions lie in robotic ultrasound systems (RUSs), where he has tackled one of the field's central challenges: achieving stable, adaptive scanning on complex and uncertain human body surfaces. His 2023 paper on Inverse Reinforcement Learning-based active compliance control has already garnered 40 citations, demonstrating the field's rapid uptake of his approach to automating repetitive clinical procedures while reducing operator workload. Complementing this, his autonomous vascular imaging system — cited 25 times — introduced a decoupled control strategy enabling reliable ultrasound diagnosis without external vision systems, a significant step toward clinical deployability. More recently, Liang has expanded into 3D endoscopic imaging, proposing a compact monocular dual-view system using dichroic prisms that promises to overcome the physical limitations of conventional binocular endoscopes in minimally invasive surgery. Across his body of work, Liang consistently bridges robotics, medical imaging, and machine learning to create practical solutions that enhance clinical precision and autonomy.