�ֲ���ý��Ƶ

My interdisciplinary research integrates advancements in health sciences, artificial intelligence & machine learning, and digital technologies to address critical issues in the construction industry. With my collaborators, I have explored several key areas: (1) real-time location monitoring using ultra-wide band sensors, (2) ergonomic evaluation of workers using electromyography & motion sensors, (3) investigating factors leading to fall accidents using force-plate and inertial measurement units, (4) mental fatigue monitoring with eye-tracking technology, electroencephalography, and computer vision sensors, and (5) physical fatigue prediction for construction workers using physiological and computer vision sensors. Some notable outputs from these research endeavors include: (1) Development of a tool to monitor balance of construction workers, (2) A novel methodology to assess fatigue using heart rate variability metrics, (3) Fatigue monitoring by fusing vision and foot-pressure sensors using inverse dynamic modelling. My current work focuses on: (1) augmented reality and Vision-Language Models (VLMs) powered solutions, (2) developing human-robot collaboration tools, and (3) exploring innovative methods for accurate fatigue monitoring.

I have worked on several funded research projects as PI and co-PI with a combined funding of over £300,000. These projects were funded by Innovate UK, Research Grant Council of Hong Kong and Ministry of Higher Education, Saudi Arabia.