
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