Research
Our laboratory develops computational and data-driven approaches for understanding and designing materials and molecular systems. We combine first-principles calculations, molecular dynamics and coarse-grained simulations, quantum chemistry, and machine learning to uncover structure–property relationships across multiple scales. Our research covers a broad range of systems, including polymer and membrane materials, low-dimensional and moiré materials, and biomolecular systems relevant to drug discovery. We also develop materials informatics and AI methodologies that integrate simulation data, experimental data, and scientific knowledge for prediction, optimization, and discovery. Through collaborations with experimental researchers, we aim to establish computational frameworks that accelerate materials and molecular design.
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