eSupervisor Detail

About me

I am a computational mechanics researcher with a strong background in finite element analysis, constitutive modeling, and simulations. I specialized in modelling and FEA approaches for predictions. As a mentor, I aim to provide students with rigorous training in computational mechanics, programming, and research methodology, while fostering critical thinking, interdisciplinary collaboration, and the ability to translate simulations into practical engineering and biomedical applications.

Interests: My research interests lie in computational solid mechanics, biomechanics, and data-driven modeling, with a focus on developing predictive, physics-informed simulation frameworks for complex material and biological systems. I specialize in finite element analysis (FEA), constitutive model development, and inverse parameter identification, integrating experimental measurements and medical imaging (e.g., CT/image-based modeling) to build realistic, patient- or material-specific computational models. My work emphasizes understanding process–structure–property relationships through simulation-driven design and validation. A central theme of my research is the mechanical characterization and modeling of biological and soft materials, including bone and biomimetic structures, where I combine imaging, additive manufacturing, and mechanical testing with numerical simulations to evaluate performance. I have experience implementing rate- and damage-dependent constitutive laws (e.g., Johnson–Cook, Cowper–Symonds, and modified models), performing multiphysics and nonlinear analyses, and developing data-assisted or physics-informed approaches to enhance model accuracy and computational efficiency. Moving forward, I aim to advance personalized and real-time computational modeling, digital twins, and machine learning–augmented mechanics frameworks, with applications in biomedical engineering, orthopaedics, and advanced materials design.