Bruce Ferry

Papers

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About

Bruce Ferry’s research lies at the intersection of human-computer interaction, robotics, and automated user experience (UX) testing. His work focuses on developing scalable, machine-vision-driven systems that enable robots to autonomously interact with smart devices—from smartphones and tablets to smart TVs. Ferry’s major contributions include designing a novel automated system that combines a robotic arm with sensors to simulate human touches and clicks, allowing for large-scale, repeatable UX measurement without human intervention. This work, published in 2019, has garnered 4 citations and is foundational for automating accessibility and usability testing. In parallel, Ferry advanced deep learning techniques for robotic interaction, creating a neural network capable of detecting on-screen keyboard regions and recognizing isolated characters from camera input—a critical step toward enabling robots to auto-type on touch screens. This paper, also from 2019, has 2 citations and addresses a key gap in interactive robotics. Ferry’s research is notable for bridging computer vision and physical robotics, offering practical tools for industry and academia alike. His work promises to streamline how we evaluate and improve user interfaces at scale, making technology more intuitive and accessible.