Jian Hou

Imperial College London, Liaoning Shihua University

Papers

Total Citations

H-Index

About

Jian Hou is a robotics researcher whose work bridges the critical gap between practical hardware design and intelligent perception systems. His primary research areas include tactile sensing, robotic manipulation, and deep learning-based computer vision. Hou’s most significant contribution is the development of a cost-efficient and repairable barometric tactile sensor array, detailed in his 2024 paper (7 citations). By keeping material costs under 80 USD and avoiding the common pitfall of molding rubber directly over barometers, he has created a robust, repairable solution that directly addresses the high cost and fragility that have long limited tactile sensor adoption in robotics. This work has the potential to democratize tactile sensing for research and industry. Complementing this hardware innovation, Hou also tackles the challenge of robotic perception in cluttered environments. His 2021 paper (7 citations) improves the SSD deep learning algorithm to accurately recognize workpieces that are randomly placed and stacked, solving a classic problem in industrial machine vision. Through these dual contributions in affordable hardware and robust software, Jian Hou is advancing the practical deployment of robots in real-world, unstructured settings.