Jingya Wang

Papers

Total Citations

H-Index

About

Jingya Wang is an emerging researcher specializing in computer vision, human motion analysis, and intelligent sensing systems. Her work sits at the intersection of multimedia computing and real-world human identification, with a particular focus on leveraging advanced sensor technologies to solve practical recognition challenges. Her most notable contribution, "Gait Recognition in Large-scale Free Environment via Single LiDAR" (2022), demonstrates her innovative approach to biometric identification — using LiDAR's depth-sensing capabilities to recognize individuals through their unique walking patterns without requiring direct interaction or cooperation from subjects. This research holds significant implications for smart home systems, healthcare monitoring, and non-intrusive security applications, reflecting Wang's commitment to developing technologies that operate seamlessly in unconstrained, real-world environments. The work has already garnered 10 citations, signaling growing interest from the research community in LiDAR-based human analysis methodologies. Wang's research profile reveals a researcher pushing the boundaries of contactless human identification, combining expertise in sensor fusion, multimedia systems, and machine learning to address fundamental challenges in how intelligent systems perceive and recognize human behavior across diverse environments.