Research Areas

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

  • Bayesian inference

  • Extensions to multiple temporal scales and spatial processes

  • Applications in ecology, environment, astronomy, sports + health

Bayesian Inference

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.

Animal Movement

Identification of animal behaviors from accelerometer, positional and/or acoustic data.

sharks - sheep - lizards - snakes - fish

Spatial Statistics

Point processes for animal movement.

Shark Statistics

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.