Research vision

I am a computational materials scientist integrating first-principles electronic structure methods, materials-focused machine learning, and variational quantum algorithms to address computational bottlenecks in materials and molecular systems. My work spans density functional theory, quantum chemistry, and quantum simulation, with particular emphasis on active-space design, algorithmic benchmarking, and reproducible hybrid classical–quantum workflows. I focus on chemically and energetically relevant systems where conventional approaches become computationally intensive or lack interpretability, and where quantum-enhanced strategies may offer scalable alternatives. My research aims to develop coherent frameworks that unify predictive modeling, quantum algorithm development, and experimentally meaningful materials problems.