Kun Lan

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About

Kun Lan is a researcher at the forefront of intelligent sensing and industrial automation, with key contributions spanning flexible tactile sensing, machine learning for biomedical applications, and computer vision for advanced manufacturing. Lan’s most notable work includes the development of a highly sensitive and robust capacitive tactile sensing array using a micro-structured porous dielectric layer, achieving both high sensitivity and stable performance across a broad pressure range—critical for electronic skin applications in detecting human motion dynamics. This work has garnered 9 citations and represents a significant step toward practical, durable e-skin. In parallel, Lan has applied broad learning systems with attribute selection to rheumatoid arthritis diagnosis (6 citations), demonstrating expertise in feature extraction and medical signal processing. Most recently, Lan’s deep learning-based multi-scale feature fusion system addresses complex challenges in precision welding robots, such as variable lighting and metal spatter, enhancing defect detection for high-end manufacturing. With a growing citation impact and work spanning from biomedical computing to industrial robotics, Kun Lan is establishing a reputation for translating advanced algorithms into real-world sensing and automation solutions.