PhD Title: Optimising power grids and chemical reactions with graph neural networks

PhD Supervisor: Albert Bartok-Partay

In this project the wider applicability of graph neural networks will be explored, to answer questions as "How do atoms arrange in space to form molecules and materials?" and "How does power flow in an electrical grid?". The common theme is that both problems may be represented as graphs: atoms or substations as the vertices, and bonds or transmission lines as the edges. GNNs will be employed to model interactions in such systems and to optimise processes. Results of this work will be useful in optimising electricity grid operations and schedules as well as in understanding chemical transitions between different molecules.