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—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!