📍 Specialising in predictive modelling, Bayesian statistics, and machine learning applied to agriculture, ecology, and animal health.
🔬 My research focuses on:
- Disease Prediction: Building models to predict and mitigate outbreaks in livestock, with a focus on diseases like BVD.
- Machine Learning: Developing advanced classifiers, anomaly detectors, and survival analysis methods for imbalanced datasets.
- Bayesian Methods: Extending hierarchical models for population estimation and disease monitoring.
🛠️ Passionate about creating accessible tools for researchers, including R packages for statistical modelling and data visualisation.
📊 Stats blogger @Simplifying Statistics, making complex statistical concepts easy to understand, and sharing some of my current projects.
💡 Projects:
- Multi-stage BVD prediction models.
- R package development (e.g., multi-species N-mixture models).
- Digitising and exploring historical data (e.g., John Snow's 1854 cholera map, Minard's map of Napoleon's march).
🌱 Always learning and exploring new ways to apply statistics to real-world problems.
Email me at: [email protected]
Or connect with me on:
Google Scholar
LinkedIn