Teaching
Teaching materials will be developed around condensed matter physics, computational materials, quantum materials, and AI/ML-based methods.
Planned courses and training directions
Computational condensed matter physics
First-principles calculations, band structures, density of states, Wannier functions, and effective models.
First-principles calculations, band structures, density of states, Wannier functions, and effective models.
AI/ML methods for materials
Materials data, physics-informed descriptors, machine-learning models, interpretability, and materials screening.
Materials data, physics-informed descriptors, machine-learning models, interpretability, and materials screening.
Research training
Literature reading, coding practice, computational workflows, and scientific communication for undergraduate and graduate students.
Literature reading, coding practice, computational workflows, and scientific communication for undergraduate and graduate students.
Future plans
The group will gradually organize lecture notes, computational tutorials, code templates, and student research-training projects to help new members get started efficiently.