The objects of our group's research are functional electronic and optoelectronic materials and related systems (surfaces, interfaces, defects, and alloys), which are in most cases solid-state matter that can be described in terms of three- or two-dimensional periodicity in space. Today, the performance (efficiency, stability, wave length and monochromaticity of emission, etc.) of devices based on these materials is closely related to their properties on nanoscale, i.e., crystal structure, atomic structure, and electronic structure. Quantum mechanical first-principles (ab initio) modeling is fundamental to explore these properties. The success of Density-functional-theory (DFT) provides a most efficient or even the only available method to handel these problems, as it can properly balance the computational accuracy and expense. However, the complexity of "advanced materials systems" induces big challenge of applying conventional DFT because of the complexity in materials systems, especially the phenomena of disorder, including chemical disorder induced by (quasi)random alignment of multiple species occupying the same lattice sites, and structural disorder reflected by the energetically favored structural distortion. Machine learning techniques are thus employed to integrate DFT calculation data to overcome or circumvent these problems.

The research profile of our group can be summarized according to different classifications as follows: