Current Research Interests

1. STATISTICAL MODELING OF INFECTIOUS DISEASE

• Diseases of humans, animals and plants
• Spatial systems
• Network-based systems
• Measurement error & latent information
• Robustness to assumptions
• Computational methodologies (see Bayesian & Computational Statistics below)
• Study design
• Model comparison
• Model adequacy/goodness of fit
• Disease surveillance models

2. BAYESIAN AND COMPUTATIONAL STATISTICS

• Markov chain Monte Carlo methods (MCMC)
• Approximate Bayesian computation (ABC)
• Gaussian process emulation
• Machine learning-based approximate inference
• Importance sampling and sequential Monte Carlo (SMC)

3. ECOLOGICAL AND ENVIRONMENTAL MODELING

• Spatial and spatiotemporal models (e.g. disease mapping)
• Invasive species models (e.g. Ash borer, Pine beetle, Giant hogweed)
• Fire spread models
• Animal movement models

4. EXPERIMENTAL DESIGN

• Bayesian experimental design
• Crop trials (e.g. dealing with inter-plot interference in experiments on crop diseases)
• Spatial design for experiments used to ascertain infectious disease dynamics
• Response surface methodology and optimal design

5. STATISTICAL & MACHINE LEARNING

• Random forests & ensemble methods
• Networks and deep learning
• High dimensional model selection (e.g. gene selection)
• Predictive modelling and classification

6. OTHER TOPICS

• Bayesian clinical trials
• Network meta-analyses
• Discrete choice experiments

Tags: Robert Deardon