Kate Ching‐Ju Lin

National Yang Ming Chiao Tung University

Papers

Total Citations

H-Index

About

Kate Ching-Ju Lin is a leading researcher at the intersection of wireless networking, mobile computing, and IoT, with a focus on enabling intelligent, context-aware automation. Her work addresses critical challenges in indoor localization and person identification, where traditional GPS and biometrics often fail due to environmental constraints. In her highly cited 2020 paper, she pioneered a novel magnetic field-based localization system for factories, using neural networks and robotic sampling to achieve robust positioning without GPS—a key enabler for Industry 4.0. Lin also made significant contributions to sensor fusion, developing methods that combine depth cameras and inertial sensors for reliable person identification, as demonstrated in her 2018 and 2019 works. These papers, with 34, 18, and 15 citations respectively, showcase her ability to integrate visual and inertial data for identity-aware tracking, overcoming limitations of lighting and obstacles. Her research has profound implications for smart factories, autonomous robotics, and pervasive computing, establishing her as a key innovator in practical, deployable sensing systems.