Dimitri Domnjuk

About the person

I investigate how the complex physics of molecules can be translated into mathematically structured, learnable, and interpretable representations. For this, I develop new models that go beyond classical message-passing graph neural networks and are specifically designed to capture the relevant structural and geometric patterns. In doing so, I integrate concepts from graph theory, logic, statistical learning and quantum chemistry.