My research focuses on emergent phenomena in quantum materials, seeking to understand how collective behavior arises from the interplay of electronic correlations, band topology, and quantum geometry.

A complementary direction of my research is the development of machine-learning methods for quantum physics. I am especially interested in AI-based variational techniques and computational tools for investigating complex many-body systems. My broader interests include physics-informed neural networks and learning frameworks in which physical laws, symmetries, and experimentally relevant constraints are incorporated directly into the model.