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About

Duc My Vo is a researcher specializing in human-robot interaction, computer vision, and real-time perception systems for mobile robotics. Their work focuses on developing robust algorithms that enable robots to reliably detect, track, and recognize humans in complex, real-world environments — addressing challenges such as varying illumination conditions, dynamic human poses, and frequent occlusion. Vo's most impactful contribution is a 2014 algorithm leveraging RGB-D imagery for real-time person detection and tracking on mobile robots, a paper that has garnered 13 citations and represents a meaningful step forward in making robots more socially aware and responsive. Building on this foundation, Vo has also advanced the field of face recognition for mobile platforms, developing techniques that combine Local Ternary Patterns with Collaborative Representation-Based Classification to achieve reliable, real-time identification — work published in both 2015 and 2016. Taken together, Vo's research addresses a critical bottleneck in robotics: equipping mobile systems with the perceptual intelligence needed for seamless human interaction. For students and researchers working at the intersection of computer vision and autonomous systems, Vo's contributions offer practical, implementable solutions to some of the field's most persistent challenges.