Simon Rolph is a data scientist and statistical ecologist with a decade of experience applying data-driven methods to biodiversity monitoring and conservation. Based at UKCEH, he builds scalable geospatial and modelling pipelines (including containerised R services on JASMIN) to run species distribution models for hundreds of taxa and to enable adaptive sampling and citizen science at large scales. He led an experiment with 850+ participants testing personalised “data story” emails to change volunteer behaviour and co-designs engagement with citizen scientists, blending social insight with technical delivery. His work spans machine learning for acoustic bird ID, automated digital twins for biodiversity, and practical deployments for partners such as Network Rail and regional Wildlife Trusts. Trained to PhD level in statistical ecology, he combines rigorous research methods with production-ready software practices to turn complex ecological problems into actionable monitoring systems.
10 years of coding experience
Doctor of Philosophy (Ph.D.), Statistical Ecology, Doctor of Philosophy (Ph.D.), Statistical Ecology at The University of Sheffield
Bachelor's degree, Conservation Biology and Ecology, 1st Class, Bachelor's degree, Conservation Biology and Ecology, 1st Class at University of Exeter
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