Zefeng Wang

Hautes Études d'Ingénieur, Sorbonne Université

Papers

Total Citations

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About

Zefeng Wang’s research lies at the intersection of assistive robotics and human-robot interaction, with a particular focus on leveraging robotic platforms to improve human mobility and communication. His most cited work, “Slow walking model for children with multiple disabilities via an application of humanoid robot” (2015, 18 citations), introduces a pioneering approach that uses humanoid robots to model and facilitate slow, stable walking patterns for children with complex physical impairments. This contribution directly addresses a critical gap in rehabilitation robotics, offering a non-intrusive, engaging method to support motor skill development. Wang also made notable strides in auditory interfaces with his work on “Binaural Speaker Recognition for humanoid robots” (2010, 4 citations), which tackles the underexplored challenge of automatic speaker recognition in binaural contexts. By enabling robots to identify speakers using spatial audio cues, this research enhances the naturalness of speech-based human-robot interaction—a key step toward more intuitive robotic companions. Though his citation counts are modest, Wang’s work demonstrates a thoughtful, application-driven approach, blending robotics, signal processing, and rehabilitation science to create technologies that directly benefit vulnerable populations. His contributions are particularly valuable for researchers exploring inclusive robotics and assistive technologies.