Research

My current work at Cardiff studies NLP models that use graph representations and reasoning, with GPU-accelerated training and evaluation in PyTorch.

• Language models and structured representations
• Graph-based reasoning
• Reproducible Python, PyTorch, and CUDA workflows

I develop spectral tools for graph comparison and clustering, including magnetic Laplacians, spectral bracketing, and constrained graph clustering.

• Discrete magnetic Laplacians
• Spectral clustering and graph comparison
• Isospectral graphs and spectral bracketing

I design entropy and complexity measures for signals on networks, with applications to EEG, fMRI, DTI, sensor, and flow data.

• Graph-signal entropy and complexity
• EEG, fMRI, and DTI networks
• Noisy multivariate and sensor data

At INEE in Mexico, I worked with national assessment and census data, combining statistical modelling, GIS analysis, and dashboards for policy teams.

• National educational assessment and census data
• Multilevel modelling and graph-based clustering
• Reproducible R workflows, GIS maps, and Shiny dashboards