As a group, our research interests span many areas, from foundational statistical properties + computation to modeling ecological and other types of remotely collected sensor data. Below is an overview of the general research areas of current interest:
Hidden Markov Models (HMMs)
HMMs in Statistical Ecology/for animal movement
Inference under multimodal posteriors
Extensions to multiple temporal scales and spatial processes
Applications in ecology, environment, astronomy, sports + health
The B.E.E.S. group functions under a Bayesian bend, with a focus on prior specification, identifiability and model misspecification and all the fun it leads to.
Identification of animal behaviors from accelerometer, positional and/or acoustic data.
sharks - sheep - lizards - snakes - fish
Point processes for animal movement.
Advanced statistical modeling for complex shark data collected over time and space.
*Keen to take students on with a strong math background and interest in modeling complex shark data.