NLP and graph representation learning
NLP methods that use graph representations and reasoning, with reproducible PyTorch experiments.
Postdoctoral Researcher · Cardiff University
Graphs, signals, and machine learning.
I work on NLP and graph representation learning at Cardiff University. My research spans graph-based learning, scalable clustering and biomedical signals, with reproducible experiments in Python and PyTorch.
NLP methods that use graph representations and reasoning, with reproducible PyTorch experiments.
Spectral tools for graph comparison, community detection and constrained clustering.
Entropy and complexity measures for EEG, fMRI and other signals on networks.
Statistical models, GIS maps and R/Shiny dashboards for national education data.
International Conference on Machine Learning (ICML), 2025
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
IEEE Transactions on Signal and Information Processing over Networks, 2022
23 research talks across nine countries, in graph theory, signal processing, and network science.
250+ contact hours, three MSc co-supervisions, and a Teaching Excellence Award.
Courses and supervisionFor correspondence and other enquiries, please get in touch.