Associate Professor, Jiaxing University, China.
Dr. Chao Yang, born in 1982, is currently a Lecturer in the School of Mechanical Engineering at Jiaxing University, China. He holds a Ph.D. in Mechanical Engineering from Zhejiang Sci-Tech University (2019), preceded by an M.E. in Engineering Mechanics from Dalian University of Technology (2009) and a B.E. in Process Equipment & Control Engineering from Zhengzhou University of Light Industry (2005). Since joining academia, Dr. Yang has consistently contributed to advancing the mechanics of parallel manipulators, focusing on kinematics, dynamics, stiffness analysis, and intelligent optimization algorithms. With over 20 peer-reviewed publications in reputable international journals and Awards, he has become a recognized figure in robot modeling and design. Dr. Yang also serves as a reviewer for journals like Mechanism and Machine Theory and Applied Mathematical Modelling, further reflecting his deep academic engagement. His work bridges theoretical innovation and practical engineering applications in robotics and precision mechanisms.
🧾Author Profile
🏆 Strengths for the Award
1. Deep Specialization in Parallel Manipulators
Dr. Yang’s research is highly focused and impactful in the domains of kinematics, stiffness modeling, dynamics, and optimization of parallel manipulators. His work addresses both theoretical foundations and practical design aspects, which are critical to modern robotics and automation systems.
2. Robust and Consistent Publication Record
Since 2018, Dr. Yang has published 20+ peer-reviewed articles, many in high-impact international journals such as:
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Mechanism and Machine Theory
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Mechanical Sciences
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Chinese Journal of Mechanical Engineering
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Robotica
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International Journal of Control
3. Novel Contributions in Modeling Techniques
Dr. Yang has proposed and validated novel methodologies including:
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Elastodynamic and elastostatic modeling of over-constrained systems
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Use of neural networks and principal component analysis for multi-objective optimization
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Finite-time tracking control techniques for underwater vehicles
These show innovation, interdisciplinary thinking, and a mastery of mechanical system modeling.
4. International Journal Reviewership
Dr. Yang serves as a reviewer for journals like Applied Mathematical Modelling and Mechanism and Machine Theory, which reflects recognition of his expertise by the academic community.
🎓 Education
Dr. Chao Yang began his academic journey in mechanical disciplines with a Bachelor’s degree in Process Equipment & Control Engineering from Zhengzhou University of Light Industry, China, in 2005. He continued to sharpen his analytical and mathematical expertise by completing his Master’s in Engineering Mechanics at Dalian University of Technology in 2009, where he laid the groundwork for his future in dynamic systems and mechanical modeling. In 2019, he earned his Ph.D. in Mechanical Engineering from Zhejiang Sci-Tech University, focusing on advanced dynamic analysis and optimization techniques for parallel robotic manipulators. His academic training integrates control theory, mechanical design, and computational modeling—making him uniquely positioned to tackle cutting-edge problems in modern robotics. This rich educational background directly contributes to his current research, which blends multi-body dynamics, elastostatics, and AI-based optimization in robotic mechanisms.
Dr. Chao Yang’s research focuses on the mechanics, modeling, and optimization of parallel manipulators—key elements in robotics and precision automation. His work revolves around four core themes: kinematics, stiffness modeling, dynamic analysis, and multi-objective optimization. He explores how over-constrained or hybrid manipulator systems can be optimized using neural networks, principal component analysis, and evolutionary algorithms. His innovative modeling methods extend to both elastostatic and elastodynamic domains, enabling more precise and adaptive control systems. He also delves into applications such as underwater robotics and hybrid robot platforms. By avoiding Lagrangian multipliers in modeling and adopting screw theory in kinetostatic design, he simplifies computational complexity while maintaining physical accuracy. His contributions fill a crucial gap in designing robust, high-performance robotic systems that are used in manufacturing, aerospace, and intelligent automation. Dr. Yang’s research is practical, interdisciplinary, and driven by the demands of next-generation robotics.
📚 Publications Top Notes
1. A hybrid algorithm for the dimensional synthesis of parallel manipulators
Journal: Proc. IMechE Part C: Journal of Mechanical Engineering Science, 2025
Authors: Yang, C.; Zhang, H.; Huang, F.; Ye, W.
Summary: This study presents a novel hybrid algorithm integrating evolutionary computing and deterministic search for optimizing the geometry of parallel manipulators. It addresses trade-offs in workspace, stiffness, and dexterity with improved computational performance.
2. Elastodynamic modeling and analysis of a 4SRRR overconstrained parallel robot
Journal: Mechanical Sciences, 2025
Authors: Wang, B.; Zhao, Y.; Yang, C.; Hu, X.; Zhao, Y.
Summary: Investigates vibration and dynamic response of a 4SRRR parallel robot. The study contributes to better understanding structural deformation under motion, crucial for high-speed precision applications.
3. Kinematic Analysis and Optimization Design of 2-PRU-PRRPa Parallel Mechanism
Journal: Transactions of the Chinese Society for Agricultural Machinery, 2025
Authors: Zhang, W.; Feng, S.; Yuan, X.; Sun, P.; Yang, C.; Lu, Y.
Summary: Offers a systematic study of a novel parallel mechanism applied in agricultural automation, optimizing motion paths and actuator placement.
4. Multibody elastodynamic modeling of parallel manipulators based on the Lagrangian equations without Lagrangian multipliers
Journal: Proc. IMechE Part C: Journal of Mechanical Engineering Science, 2025
Authors: Gong, Y.; Lou, J.; Yang, C.; Ye, W.
Summary: This paper introduces a novel elastodynamic modeling approach for parallel manipulators that bypasses the use of Lagrangian multipliers. The methodology improves numerical efficiency and simplifies model derivation, making it suitable for real-time control and simulation of complex parallel robotic systems.
5. Dynamic modeling and performance analysis of the 2PRU-PUU parallel mechanism
Journal: Mechanical Sciences, 2024
Authors: Sun, T.; Ye, W.; Yang, C.; Huang, F.
Summary: Focuses on the dynamic modeling of a 2PRU-PUU architecture parallel robot. Through simulation and performance metrics evaluation, the study demonstrates how structural configurations affect system response and highlights its suitability for precision tasks in constrained workspaces.
Conclusion
Dr. Chao Yang is highly suitable for the Research for Best Researcher Award—particularly in domains of mechanical systems design, parallel robots, and multi-objective optimization. His contributions are academically rich, technically deep, and steadily expanding. While early in his career stage as a lecturer, the maturity and depth of his publication portfolio, coupled with innovative methodologies, clearly reflect a rising star in mechanical engineering research.
