Experience

Developing mathematical theory and algorithms for curved high-order meshing and (hp/r)-adaptivity to improve the accuracy and efficiency of finite element methods.

Designing a scalable software architecture for the practical implementation of adaptive high-order FEM frameworks.

Developed a Python-based tool to generate computational meshes from MRI/CT-derived STL files for realistic biomedical geometries.

Integrated geometry processing and meshing workflows to support patient-specific numerical simulations.

Developed and analysed adaptive-mesh-refinement finite-element methods for cancer modelling and drug–tissue interaction models.

Implemented time-adaptive numerical strategies to improve simulation accuracy and computational efficiency.

Designed parallel computational frameworks for large-scale biomedical simulations.

Incorporated realistic patient geometries to enhance the clinical relevance of the models.

Applied advanced a posteriori error control techniques to guide mesh refinement and ensure reliable numerical results.

Designed novel time-integration schemes for stiff partial differential equations, including the compressible Navier–Stokes equations and reaction–diffusion systems.

Developed higher-order hybrid compact schemes on non-uniform grids for simulating non-periodic flow problems.

Studied complex pattern formation and nonlinear dynamics in reaction–diffusion systems.

Assisted in teaching core undergraduate and graduate courses, including Numerical Methods, Finite Element Methods, and Computational Fluid Dynamics.

Investigated well-posed formulations and operator-splitting techniques for large-scale rotary-flow simulations.

Successfully bridged mathematical theory and high-performance computation.