Xiaohui Duan

Papers

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About

Xiaohui Duan is a robotics researcher whose work sits at the intersection of computer vision, deep learning, and human-robot interaction. Her key research areas include robotic art creation, autonomous control systems, and assistive robotics for elderly care. Duan made a notable contribution to robotic artistry with her 2019 paper on a portrait pencil-sketching algorithm that incorporates face component and texture segmentation, a novel approach that enriches robotic painting with semantic information. In 2018, she pioneered the use of Deep Q Networks (DQN) for robotic auto-focus systems, demonstrating an end-to-end deep reinforcement learning method that outperforms traditional techniques. Her 2021 work on vision-based fall detection for mobile robots addresses a critical healthcare challenge, proposing a deep learning framework to detect falls in elderly individuals living alone. With each of her most-cited papers garnering over 10 citations, Duan’s research is gaining traction for its practical applications. Her ability to blend artistic expression with robust engineering, and to tackle real-world problems like elder safety, marks her as an innovative voice in modern robotics.