Doctor | Hohai University | China
Dr. Jun Xie, currently a postdoctoral researcher at the College of Mechanics and Engineering Science, Hohai University, earned his Ph.D. in Applied Mathematics from Ningxia University in 2024. His research specializes in the multi-field coupling mechanical behavior of intelligent materials, particularly focusing on the safety performance and optimization of functionally graded composite materials and structures under multi-physical environments. Dr. Xie has made significant advances in the analytical and numerical modeling of magnetoelectric (ME) effects in layered functionally graded piezoelectric/piezomagnetic (FGPEPM) spherical shells. His work derives closed-form solutions under power-law volume fraction gradients and applies the finite difference method (FDM) for arbitrary gradients. To address material property uncertainties, he introduced a novel interval random uncertainty model and developed a deep neural network (NN) framework that serves as a high-precision, computationally efficient surrogate for uncertainty quantification and optimization. This approach significantly reduces computational costs compared to traditional methods while maintaining predictive accuracy, marking a major contribution to intelligent materials research. Dr. Xie’s ongoing projects include the Fundamental Research Funds for the Central Universities (No. B250201171) and the Jiangsu Funding Program for Excellent Postdoctoral Talent (No. 2025ZB867). He has published 21 peer-reviewed SCI papers in high-impact journals such as Composite Structures, Applied Mathematical Modelling, and Thin-Walled Structures. Notably, his 2025 article in Thin-Walled Structures has received 154 citations. As of now, Dr. Xie holds an h-index of 7, reflecting the growing impact and recognition of his contributions to the field of multi-field coupling mechanics.
Profile: Scopus
Featured Publication
1.Data‑driven deep neural network approach for magnetoelectric effects in functionally graded piezoelectric/piezomagnetic spherical shells with material parameters uncertainties. (2026). Thin Walled Structures.
2. Xie, J., Gou, X., & Shi, P. (2025). Exact solutions for the linear hardening elastoplastic model in functionally graded spherical shell. Composite Structures.
Cited by 1.
