Xiaoying Zhuang
Papers
1
Total Citations
5
H-Index
1
About
Xiaoying Zhuang is a leading researcher in computational mechanics, with a focus on developing advanced numerical methods for complex material and structural behavior. Her key research areas include large deformation analysis, hyperelasticity, and the innovative application of Physics-Informed Neural Networks (PINNs) to solve challenging engineering problems. Zhuang’s major contributions lie in bridging traditional continuum mechanics with modern machine learning, as exemplified by her highly cited 2025 paper on the large deformation analysis of inhomogeneous hyperelastic thick-walled spheres under internal and external pressure. This work introduces a novel PINN-based framework that effectively handles nonlinear material behavior, geometric constraints, and spatially varying properties—issues that have long posed significant challenges in the field. With over 5 citations already for this recent publication, her impact is rapidly growing among researchers in computational solid mechanics. Zhuang’s work is notable for its practical relevance to aerospace, biomedical, and civil engineering applications, where accurate modeling of soft materials and complex loading conditions is critical. Her pioneering integration of physics-informed deep learning with classical mechanics positions her as a key figure in the next generation of computational methods.
Research Focus
Key Achievements
Top Papers
- 1