Xijun Zhang

Qingdao University of Science and Technology

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About

Xijun Zhang is a pioneering researcher at the intersection of artificial intelligence and advanced manufacturing. His primary research areas include machine learning applications in 3D printing, additive manufacturing process optimization, and intelligent materials design. Zhang’s major contribution lies in his comprehensive review "Machine learning-driven 3D printing: A review" (2024), which has already garnered 57 citations, establishing a foundational framework for integrating AI algorithms with additive manufacturing technologies. This work systematically analyzes how machine learning can enhance print quality prediction, real-time defect detection, and material property optimization, bridging critical gaps between computational methods and practical fabrication. His research has significant implications for accelerating the development of smart manufacturing systems, enabling adaptive process control, and reducing material waste. Zhang’s ability to synthesize complex interdisciplinary concepts has made his work highly influential among both academic researchers and industry practitioners. As one of the emerging voices in Industry 4.0, his ongoing investigations into AI-driven design-to-production workflows promise to reshape how complex geometries and functional materials are realized through additive processes.