People

Room: 215

I'm interested in the development of new graph generation models, and their applications them to various fields such as molecule generation. My current focus is on diffusion models.

Room: 214
I’m interested in studying the capabilities and limitations of general-purpose machine learning architectures in the context of graph learning. My current research focus is on deriving a principled understanding of graph transformers and their potential benefits over GNNs.

Room: 217
I am interested in graph learning and combinatorial optimization.

I am interested in studying the mathematical properties of Graph Neural Networks (expressiveness, optimisation methods and generalisation properties).

Currently I'm pursuing a master degree in computer engineering and supporting in research surrounding graph transformers. Previously I was working on improving a performance prediction framework in semantic segmentation.

I am a Master's student specializing in Data Science, currently focusing on transfer learning with Graph Neural Networks (GNNs) for molecular property prediction.