Max Robotics — Global Service Robot Directory + US Certification

About

Liang Yao is a leading researcher at the intersection of robotics and medical imaging, with a primary focus on autonomous ultrasound systems for clinical diagnosis. His most impactful work centers on developing intelligent robotic platforms for breast and carotid artery scanning, addressing critical challenges in full-coverage path planning and stable probe-tissue interaction. Yao’s 2022 paper on automated robotic breast ultrasound, with 51 citations, introduced a novel system that ensures complete organ coverage while maintaining consistent image quality through controlled contact forces. He further advanced the field by pioneering real-time ultrasound image quality assessment for autonomous screening (22 citations), moving beyond pixel-level statistics to enable adaptive probe adjustments. Yao’s contributions extend to reinforcement learning, where his work on efficient incremental offline learning (14 citations) and broad reinforcement learning from demonstration (12 citations) provides decision-making frameworks for high-quality imaging. His 2024 paper on carotid artery scanning with visual servo navigation (7 citations) demonstrates the versatility of his approach. By integrating robotic control, computer vision, and machine learning, Yao is transforming ultrasound from a manual, operator-dependent procedure into a standardized, autonomous screening tool, with significant implications for early cancer detection and reducing sonographer workload.