leaf_analysis_toolkit
PythonScripts for examining leaf image time-series — quantifying growth and shape change across development.
Principal Data Scientist · Cambridge, UK
Physicist by training, plant biophysicist by research, data scientist by trade. I spent a decade measuring and modelling how living tissues grow and deform — now I apply the same quantitative instinct to machine learning and healthcare data. The flock drifting behind this text is a live simulation, written from scratch — because I still like to build.
Peer-reviewed work in plant biomechanics, morphogenesis and cell-scale imaging — spanning experiment, image analysis and mathematical modelling.
Source: Google Scholar
Full list, metrics and co-authors on Google Scholar and ResearchGate.
Open-source scientific tooling and side projects. Most of the research code below powered the analysis behind the papers above.
Scripts for examining leaf image time-series — quantifying growth and shape change across development.
A parser for JPK atomic-force-microscopy data — the measurement backbone of my cell-mechanics work.
A modified maximum-intensity-projection technique for confocal image stacks, preserving surface detail.
Reconstructs 3D meshes from segmented shoot-apical-meristem tissue images (OpenAlea).
A tiny cross-platform mouse-wiggler / anti-sleep utility. Small, but
packaged properly with uv.
Served from a Mac in my flat: dnsmasq, a dockerised nginx, a Cloudflare Tunnel, and Cloudflare Access gating private services.
Camgenium
Machine learning and statistical methods applied to healthcare and diagnostics data.
Sainsbury Laboratory, University of Cambridge
Computational and quantitative biology: live-cell imaging, image analysis, biomechanics and modelling of plant morphogenesis.
University of Sheffield
In vivo analysis of plant cell mechanics using atomic force microscopy.
University (edit)
Foundation in mathematical and computational modelling.
Open to conversations about data science, computational biology, or interesting quantitative problems.