北京大学力学与工程科学学院力学（能源与资源工程）专业2026级博士研究生，导师为邓航研究员。研究围绕地下能源与资源开发的孔隙尺度过程展开，涵盖三个相互关联的方向：颗粒材料离散元（DEM）模拟及其在低重力环境月壤力学特性中的应用；基于深度学习生成对抗网络（GAN）的多孔介质微观结构随机重构；多孔介质内反应输运过程的多物理场耦合模拟，重点关注二氧化碳矿化机理。研究致力于打通颗粒尺度力学、数据驱动结构生成与孔隙尺度过程模拟的技术链条，为地下能源工程应用提供支撑。

PhD student in Mechanics (Energy and Resources Engineering) at Peking University, supervised by Prof. Hang Deng. His research spans three interconnected themes: (1) Discrete Element Method (DEM) modeling of granular materials with applications to lunar regolith mechanics under low-gravity environments; (2) Deep learning-based generative modeling (GAN) for stochastic reconstruction of porous media microstructures; (3) Multiphysics coupling simulation of reactive transport in porous media, with a focus on CO₂ mineralization. He aims to bridge particle-scale mechanics, data-driven structure generation, and pore-scale process modeling for subsurface energy applications.