Research agenda

Computational tools for structures that can adapt.

My research combines adaptive discretization, parallel computing, and learning-based inference to make structural simulation more accurate, scalable, and useful in practice.

COMPUTATIONAL MECHANICS

Adaptive finite elements

I design error-driven h-adaptive workflows that refine the mesh where the solution needs it most, reducing discretization error without wasting computation.

Finite element analysisAdaptive meshingOpenSeesPyAbaqus
HIGH-PERFORMANCE COMPUTING

GPU-accelerated simulation

Through Python, CuPy, Numba, CUDA-oriented workflows, and multiprocessing, I build reproducible computational pipelines for structural mechanics.

PythonCuPyNumbaCUDA
SCIENTIFIC ML

Physics-informed learning

My Adaptive Mesh Growing Network direction explores element-wise material-parameter identification from sparse frequency-response measurements for structural health monitoring.

PyTorchInverse problemsFRF measurements
RESILIENT STRUCTURES

Dynamics & control

I study nonlinear dynamic response, collapse assessment, and hierarchical active damping for structural systems exposed to seismic and vibration demands.

Structural dynamicsSeismic engineeringVibration control