DGIST Scholar: 강준구

강준구

Kang, Joongoo

Researcher ID ORCiD Scopus Google Scholar Research Gate

Computational Materials Theory Group: The Computational Materials Theory Group, led by Professor Joongoo Kang, develops predictive frameworks that marry quantum mechanics, atomic-scale simulations, and machine learning to design functional materials from first principles. Our work in materials-by-design applies quantum-mechanical theory to tailor electronic, optical, and thermal properties for energy conversion and information technologies. By integrating machine-learned interatomic potentials, we uncover new physics and chemistry in complex materials systems—studying structures and dynamics beyond human intuition. In the realm of simple complexity, we employ ML-driven statistical physics and enhanced sampling methods such as metadynamics to reveal how liquids, glasses, and other disordered systems emerge from simple physical laws. Together, these approaches establish a materials-by-design paradigm that bridges fundamental theory and practical applications.

국가과학기술표준분류

12대 국가전략기술 분야