Prof. Dr. Xiaojun Liu | Digital Twin | Best Researcher Award
Professor at Southeast University, China
Professor Xiaojun Liu is a leading expert in the field of digital twin and high-performance assembly. He is a Professor and Ph.D. Supervisor at the School of Mechanical Engineering, Southeast University, where he also serves as Vice Dean. With over 50 published journal papers, 1,100+ citations, 50 patents, and significant contributions to national standards and industrial practices, Prof. Liu is recognized as a driving force behind intelligent assembly solutions for aerospace and other high-tech industries.
Publication ProfileΒ
Educational Background πΒ Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β Β
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Ph.D. in Mechanical Engineering or related field
(presumed based on position and publication record)
Professional Experience πΌ
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Vice Dean, School of Mechanical Engineering, Southeast University
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Professor and PhD Supervisor, Southeast University
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Director, Engineering Research Center for Advanced Light Source Technology and Equipment (Ministry of Education)
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Deputy Director, Jiangsu Provincial Innovation Center for High-end CNC Machine Tools
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Deputy Director, Digital Twin Professional Committee, Chinese Society for Geometric Graphics
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Chair, Award Committee, Digital Twin International Conference (2022β2024)
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Conference Chair, 6th Academic Conference on Digital Twin and Intelligent Manufacturing Services
Research Interests π¬
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Digital Twin Systems
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High-Performance Assembly Processes
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Human-Robot Collaboration in Industry 5.0
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Process Monitoring and Adaptive Control
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Application of AI and LLMs in Manufacturing Systems
Awards and Honorsπβ¨
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National Science and Technology Progress Award
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Multiple Provincial-Level Science and Technology Awards
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Chaired and participated in numerous national-level research grants, including:
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National Key R&D Programs (e.g., 2023YFE0198600, 2020YFB1708400)
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NSFC-funded projects (e.g., U24B2064, U22A20201)
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Editorial Board Member, Digital Engineering
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International Advisory Committee Member, Digital Twin
Conclusionπ
Professor Xiaojun Liu stands out as a pioneer in integrating digital twin technology with high-precision assembly systems. His academic contributions, leadership in national research initiatives, and influential roles in professional organizations make him a distinguished candidate for the Best Researcher Award. His work has bridged theoretical innovation and industrial application, making substantial impacts in aerospace, CNC machinery, and intelligent manufacturing.
Publications π
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An LLM-guided SD-LDM Digital Twin Construction Strategy (LSDT) for multi-industrial scenarios: Enhancing adaptability and efficiency
βοΈ F. Wang, X. Liu, F. Lv, X. Zheng, C. Li
π Journal of Manufacturing Systems, 2025
π’ Citations: 0
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A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability
βοΈ X. Liu, C. Wang, F. Wang, F. Feng, Y. Sun
π Journal of Manufacturing Systems, 2025
π’ Citations: 0
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Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm
βοΈ C. Zhu, C. Wang, Z. Ni, X. Liu, A. Raza
π Mathematics, 2025
π Open Access
π’ Citations: 0
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Knowledge-driven assembly process reconfiguration method for aerospace complex products
βοΈ J. Feng, N. He, J. Liu, J. Shi, X. Liu
π CIMS, 2024
π’ Citations: 0
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Prediction and optimization method for welding quality of components in ship construction
βοΈ J. Liu, Y. Cheng, X. Jing, X. Liu, Y. Chen
π Scientific Reports, 2024
π Open Access
π’ Citations: 2
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Cloud-edge-device System architecture and key technologies of industrial digital twin System based on multi-agent
βοΈ H. Li, Z. Xing, L. Li, L. Dong, Z. Wang
π CIMS, 2024
π’ Citations: 1
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Uphill directional passive transport of water droplets on axisymmetric surfaces
βοΈ J. Mo, H. Huang, C. Wang, Z. Li, X. Liu
π Physics of Fluids, 2024
π’ Citations: 0
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Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line
βοΈ J. Liu, Q. Ji, X. Zhang, X. Liu, M. Tang
π Journal of Intelligent Manufacturing, 2024
π’ Citations: 10
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Human-robot collaborative disassembly in Industry 5.0: A systematic literature review and future research agenda
βοΈ G. Yuan, X. Liu, X. Qiu, D.T. Pham, M. Su
π’ Citations: 1
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Digital twins enable shipbuilding
βοΈ J. Liu, Y. Zhang, Z. Liu, S. Gu, X. Liu
π Open Access
π’ Citations: 1