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 Profile 

Scopus

Educational Background 🎓                                                      

• Ph.D. in Mechanical Engineering or related field
  (presumed based on position and publication record)

Professional Experience 💼

• Vice Dean, School of Mechanical Engineering, Southeast University

• Professor and PhD Supervisor, Southeast University

• Director, Engineering Research Center for Advanced Light Source Technology and Equipment (Ministry of Education)

• Deputy Director, Jiangsu Provincial Innovation Center for High-end CNC Machine Tools

• Deputy Director, Digital Twin Professional Committee, Chinese Society for Geometric Graphics

• Chair, Award Committee, Digital Twin International Conference (2022–2024)

• Conference Chair, 6th Academic Conference on Digital Twin and Intelligent Manufacturing Services

Research Interests 🔬

• Digital Twin Systems

• High-Performance Assembly Processes

• Human-Robot Collaboration in Industry 5.0

• Process Monitoring and Adaptive Control

• Application of AI and LLMs in Manufacturing Systems

Awards and Honors🏆✨

• National Science and Technology Progress Award

• Multiple Provincial-Level Science and Technology Awards

• Chaired and participated in numerous national-level research grants, including:

  • National Key R&D Programs (e.g., 2023YFE0198600, 2020YFB1708400)

  • NSFC-funded projects (e.g., U24B2064, U22A20201)

• Editorial Board Member, Digital Engineering

• International Advisory Committee Member, Digital Twin

Conclusion🌟

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 📚

1. An LLM-guided SD-LDM Digital Twin Construction Strategy (LSDT) for multi-industrial scenarios: Enhancing adaptability and efficiency
   ✍️ F. Wang, X. Liu, F. Lv, X. Zheng, C. Li
   📘 Journal of Manufacturing Systems, 2025
   🔢 Citations: 0

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2. A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability
   ✍️ X. Liu, C. Wang, F. Wang, F. Feng, Y. Sun
   📘 Journal of Manufacturing Systems, 2025
   🔢 Citations: 0

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3. Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm
   ✍️ C. Zhu, C. Wang, Z. Ni, X. Liu, A. Raza
   📘 Mathematics, 2025
   🌐 Open Access
   🔢 Citations: 0

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4. Knowledge-driven assembly process reconfiguration method for aerospace complex products
   ✍️ J. Feng, N. He, J. Liu, J. Shi, X. Liu
   📘 CIMS, 2024
   🔢 Citations: 0

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5. Prediction and optimization method for welding quality of components in ship construction
   ✍️ J. Liu, Y. Cheng, X. Jing, X. Liu, Y. Chen
   📘 Scientific Reports, 2024
   🌐 Open Access
   🔢 Citations: 2

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6. Cloud-edge-device System architecture and key technologies of industrial digital twin System based on multi-agent
   ✍️ H. Li, Z. Xing, L. Li, L. Dong, Z. Wang
   📘 CIMS, 2024
   🔢 Citations: 1

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7. Uphill directional passive transport of water droplets on axisymmetric surfaces
   ✍️ J. Mo, H. Huang, C. Wang, Z. Li, X. Liu
   📘 Physics of Fluids, 2024
   🔢 Citations: 0

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8. Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line
   ✍️ J. Liu, Q. Ji, X. Zhang, X. Liu, M. Tang
   📘 Journal of Intelligent Manufacturing, 2024
   🔢 Citations: 10

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9. Human-robot collaborative disassembly in Industry 5.0: A systematic literature review and future research agenda
   ✍️ G. Yuan, X. Liu, X. Qiu, D.T. Pham, M. Su
   🔢 Citations: 1

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10. Digital twins enable shipbuilding
    ✍️ J. Liu, Y. Zhang, Z. Liu, S. Gu, X. Liu
    🌐 Open Access
    🔢 Citations: 1

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