Machine Learning

Ecosystems conceal patterns in vast, complex data. Machine learning unlocks this actionable intelligence where traditional methods fail.

Ecological data is rarely clean. I specialise in handling noisy, real-world datasets and applying advanced techniques to build models that are robust, interpretable, and trustworthy. My goal: making machine learning accessible and actionable for conservation practitioners.

I work with:

• Acoustic monitoring — species identification and habitat analysis

• Environmental DNA (eDNA) — biodiversity assessment and community profiling

• Camera trap imagery — automated species recognition and abundance estimation

• Remote sensing — habitat classification and change detection

Predictive Modelling

Tailored models that address your conservation challenges directly:

• Forecasting: predicting species abundance or range shifts under changing conditions

• Prioritisation: identifying critical areas for intervention and resource allocation

• Scenario comparison: assessing ecological impacts of different management strategies

Classification

Many conservation questions start simply: what is this, and where does it occur? I build classification models that answer these questions reliably, whether that's distinguishing species from acoustic recordings, identifying wildlife in camera trap images, or mapping habitat types from satellite imagery.

Next Step

Got a project brewing? Even if you're not sure whether it's a good fit, drop me a message and I’d be happy to chat through the possibilities!