I was awarded the Michigan Institute for Computational Discovery and Engineering (MICDE) fellowship and began joint doctoral studies in Civil (Structural) Engineering and Scientific Computing at the University of Michigan, focusing on reconfigurable structural systems for functional use. The fellowship has directly supported the computational side of my work, including funding high-performance workstations for large-scale nonlinear simulations and model development in computational mechanics.
As part of the MICDE program, I expanded my training beyond classical structural engineering into modern computational methods. I completed coursework in Machine Learning, Numerical Linear Algebra, C++ Programming, Statistics and Data Analysis, and Probabilistic Reliability of Structures. This combination of mechanics, algorithms, and data-driven methods underpins my current research, where I use numerical tools to explore how reconfigurable structures move, carry load, and can be tuned for performance.