The Liu Research Group develops next-generation computational materials science frameworks by integrating first-principles calculations, molecular dynamics simulations, machine learning interatomic potentials, and high-performance computing technologies. The group focuses on understanding atomic- and electronic-scale phenomena in materials through large-scale and high-accuracy simulations.

Current research topics include lightweight metallic materials, thermoelectric materials, organic field-effect transistors, and gas sensing materials. By combining data-driven approaches with physics-based simulations, the group investigates deformation mechanisms, thermal transport, electronic properties, and structure–property relationships in advanced materials.

A major focus of the group is the development of large-scale AI-driven atomistic simulation methods capable of bridging spatial and temporal scales beyond conventional computational limits. Through the integration of machine learning, computational mechanics, and large-scale parallel computing, the group aims to establish new computational platforms for advanced materials design and next-generation computational materials science.