Yaxin Wang

University of Glasgow, Hefei National Center for Physical Sciences at Nanoscale

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About

Yaxin Wang is a rising researcher at the forefront of advanced manufacturing and optical engineering, whose work bridges machine learning, materials science, and spatial display technologies. Wang’s key research areas include gel-based additive manufacturing, where they pioneer the integration of machine learning to accelerate material design and optimize printing processes, and chiral optical materials for next-generation spatial displays. Their most-cited work, "Machine Learning in Gel-Based Additive Manufacturing: From Material Design to Process Optimization" (2025, 25 citations), provides a comprehensive framework for using predictive algorithms to streamline gel formulation and printability—a critical step toward scalable, intelligent manufacturing. In parallel, Wang’s study on "Self-positioning microdevices enable adaptable spatial displaying" (2025, 13 citations) introduces a novel approach to extended reality by leveraging adjustable photon spin angular momentum from chiral materials. This work holds promise for applications in telemedicine, rescue operations, and space exploration. With a growing citation footprint and a focus on unconventional form factors, Wang is establishing themselves as a key contributor to the next wave of adaptive, data-driven fabrication and immersive display systems.