Independent researcher in computational and mathematical biology

I work across computational biology, mathematical biology and pure mathematics. I use models, public biological data and reproducible software to study sequences, regulation, proteins, cell states and disease. I care about the boundary between what a calculation establishes and what still needs biological validation.

• RNA and gene regulation: synonymous sequence spaces, RNA structure, perturbation experiments and transcriptional response.
• Cancer and cell states: single-cell and spatial transcriptomics, glioblastoma tissue geometry, and synthetic ctDNA decision-model simulations.
• Protein science: bacteriocin sequence and activity analyses, protein architecture, oligomeric-state evolution and structural bioinformatics.
• Neuroscience and systems biology: stochastic neurogenesis, glutamate uptake, synaptic signalling, reaction-network simulations and bioelectric tissue models.
• Mathematics: graph and spectral methods, persistent topology and Hodge theory, molecular geometry, algebraic methods, numerical analysis and polynomial-root geometry.
• Research practice: exact enumeration where feasible, independent implementation checks, held-out evaluation, sensitivity analysis, data provenance and reproducible releases.

OpenOmicsBench is an offline collection of omics benchmarks and tools for testing bioinformatics workflows. It includes RNA-seq input packs, deterministic sequence fixtures, single-cell and genomic interval data, and reports that make checks traceable.

Browse the benchmarks · Try a worked RNA-seq example · Read the documentation

Biological data and modelling

Mathematics, statistics and validation

Most of my research code:

Also comfortable in:

Workflows and model formats

Computer algebra, topology and formal methods

The graph shows GitHub contributions over the past year and refreshes daily.

For research or software questions, email me or open an issue on the relevant project.