Jingdong Chen

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About

Jingdong Chen is a leading figure in acoustic signal processing, with a primary focus on microphone array beamforming and speech enhancement. His work is particularly critical for emerging technologies like humanoid robotics, smart speakers, and teleconferencing systems, where capturing clear speech in noisy, reverberant environments is a fundamental challenge. Chen’s major contributions lie in the rigorous analysis and development of differential beamformers, a class of algorithms that achieve high directional sensitivity with very small microphone arrays. His 2020 paper on steerable differential beamformers with planar arrays (14 citations) directly addresses the severe size and geometry constraints of arrays in humanoid robots, providing a method to dynamically focus on a human speaker. Complementing this, his 2019 work on the properties and limits of minimum-norm differential beamformers for circular arrays (9 citations) establishes the theoretical boundaries of performance for these compact systems, offering crucial design guidelines for engineers. By systematically defining the capabilities and constraints of these advanced beamforming techniques, Chen’s research provides the foundational knowledge necessary for building truly interactive and noise-robust voice-enabled devices.