Conducted research on learning and implementing structural biases in neural networks.

Supervised Master’s students:

Pim Praat (Graph-based prediction of interactions in electricity grids & analysing the importance of ego-nodes in GNNs) [April, 2024]

Elias Dubbeldam (Equivariance-learned Layers – A method to incorporate any kind of symmetry) [July, 2024]

Grade: Distinction.

Specialized in deep learning, probabilistic inference, and energy-based models (RBMs).

Grade: Distinction.

Specialized in narratology, screenwriting, AI in film and tv.

Grade: First Class (MPhys).

Started in MPhys and transfered to MMathPhys (Part C) at the Mathematics Institute.

Specialized in String Theory and General Relativity (AdS/CFT correspondence).

Final Project on Resurgence Theory (supervised by Prof. Philip Candelas).