Mingxia Chen

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About

Mingxia Chen is a pioneering researcher at the forefront of triboelectric nanogenerators and bioinspired sensory systems, with a focus on self-powered artificial intelligence for human-machine interaction. Her most cited work, "Triboelectric in-sensor deep learning for self-powered gesture recognition toward multifunctional rescue tasks" (2024, 57 citations), introduces a groundbreaking approach that integrates triboelectric sensing with in-sensor computing, enabling energy-autonomous gesture recognition for critical applications in search-and-rescue operations. Building on this, her 2025 paper on a "Bioinspired triboelectric-driven multisensory framework with autonomous cross-modal adaptation" (6 citations) draws inspiration from the human brain’s ability to synergistically process visual, tactile, auditory, olfactory, and gustatory stimuli. This framework achieves cross-modal integration, recognition, and imagination, generating comprehensive environmental representations without external power. Chen’s work uniquely bridges materials science, neuromorphic engineering, and robotics, offering transformative potential for autonomous systems in hazardous environments. Her contributions are rapidly gaining recognition for advancing self-powered, adaptive AI that mimics biological multisensory processing, positioning her as a rising leader in sustainable, intelligent sensing technologies.