Welcome

Computational Condensed Matter Physics and Materials Physics

Our group works on interdisciplinary research at the nexus of materials science, quantum chemistry, computational physics, and theoretical condensed matter physics. We are dedicated to harnessing data-driven methodologies and machine learning (ML) to understand and predict the electronic, structural, optical, mechanical, transport, and magnetic properties of advanced materials. Our research encompasses a diverse array of materials, from novel 2D structures and bulk materials to nanostructures and composites.

We employ a comprehensive suite of computational techniques, anchored by density functional theory (DFT) and first-principles-based many-body approaches. Our work is further enhanced by the integration of advanced ML algorithms and data analytics. Through these advanced computational methodologies, we strive to push the boundaries of materials science and engineering, contrtibuting to the development of next-generation materials for a wide array of applications.