Research Interests
Researcher fascinated by the emergence of neural dynamics from neural network structure and their role in behaviourally relevant computation.
I develop the theory and build mathematical tools to explore the role of higher-order inteactions and their role in driving non-linearity and compositionality in neural dynamics.
I am a group leader at University Hospital Würzburg and a Honorary Senior Research Fellow at Imperial College London.
Interests
- Graph Theory
- Geometric Deep Learning
- Neural Networks
Education
PhD in Applied Mathematics and Physical Chemistry, 2018
Imperial College London
MRes in Chemical Biology, 2014
Imperial College London
MPhys in Physics, 2012
University of Bristol
Recent Publications
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(2024).
Algorithm xxx: PyGenStability, a multiscale community detection with generalized Markov Stability.
ACM Transactions on Mathematical Software.
(2024).
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds.
The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria.
(2024).
Non-linear dynamic state-space network modeling for decoding neurodegeneration.
Neural Regeneration Research.
(2023).
A unified framework for Simplicial Kuramoto models.
arXiv preprint arXiv:2305.17977.
(2023).
Distinct phenotypes of stimulation-induced dysarthria represent different cortical networks in STN-DBS.
Parkinsonism & Related Disorders.