My academic background spans agricultural engineering, mechatronics, robotics, and manufacturing engineering. My primary research interests focus on intelligent agricultural machinery, precision agriculture, agricultural robotics, and the application of artificial intelligence and advanced sensing technologies in crop and grain assessment. My agricultural research includes maize kernel mechanical properties and breakage prediction, hyperspectral imaging for moisture, protein, starch, and hardness evaluation, machine-learning-based quality assessment, discrete element simulation, and machine-vision-guided robotic transplanting. My research also extends to intelligent manufacturing, particularly human–robot collaboration, human behaviour modelling, human motion prediction, digital twins, and adaptive robot control. I am interested in integrating machine vision, deep learning, multimodal sensing, simulation, and robotics to improve the intelligence, safety, efficiency, and sustainability of agricultural production and industrial manufacturing systems.