Shanying Li

Papers

Total Citations

H-Index

About

Shanying Li is a pioneering researcher at the intersection of robotics, acoustics, and industrial automation, with a primary focus on intelligent sound source localization and mechanical anomaly detection. Their most cited work, "Optimizing robotic collection point for accurate mechanical anomaly noise source localization within an indoor sound field environment" (2025, 3 citations), addresses a critical challenge in modern manufacturing: the difficulty of pinpointing mechanical faults in complex, reverberant indoor environments. Li’s key contribution lies in developing an optimization framework for robotic platforms that intelligently determines the optimal collection points for acoustic sensors, dramatically improving the accuracy of noise source localization. This work bridges the gap between traditional acoustic diagnostics and autonomous robotics, enabling scalable, real-time monitoring of large-scale industrial equipment. By integrating robotic mobility with advanced sound field analysis, Li has opened new pathways for predictive maintenance and quality control in smart factories. Their research is particularly notable for tackling the practical constraints of indoor acoustics—such as reflections and multipath interference—that have long hindered conventional methods. With a growing citation footprint, Shanying Li is establishing themselves as an emerging leader in robotic acoustic sensing, with implications for safer, more efficient industrial operations.