Research Interests
My Research Interests
The goal of my academic research is to bridge the gap between theory and practice. I focus on developing research questions that have practical implications for individuals, pets, and guardians, that also inform our theoretical understanding of dog behavior, cognition, and the human-animal bond. My educational background is rooted in a curiosity to understand how we, and other non-human animals, think about the world around us, while my practical background, working with dogs, aims to address behavior and cognition in real-world applied contexts.
Evaluating Applied Animal Behavior in Real-World Contexts
How do we study the behavior of our companion animals? I am fascinated by the natural behaviors of domestic dogs, and cats and the ways in which they have evolved to share our socio-ecological environment. My research evaluates questions such as:
What is the function of the play bow?
How do dogs see the world around them?
How do dogs learn?
Do dogs prefer to work for food when freely available food is present?
Will cats sit in illusory boxes and what can this tell us about their susceptibility to illusions?
Do cats and dogs make eye contact and interact with their owners?
I conduct this type of research using various methods. However, I am a strong proponent of utilizing community science research, where owners become researchers in their own home!
Replication and Collaboration in Canine Science
I am extremely invested in successful collaboration and replication. I am currently a co-founder and co-director of the ManyDogs Project an international consortium of researchers interested in canine science with the primary goal to foster global collaboration and open science practices (i.e., transparency and reproducibility) through multi-site projects. As a co-director and collection site leader for ManyDogs 1, I currently work with over 20 different research groups collecting data on canine cognition.
Can We Use Technologies to Model Dog and Human Behavior
One strategy to begin to understand human behavior and map animal behavior is to use technology. In a recent research project, in collaboration with Tech4Animals, we utilized machine learning to evaluate the activity of kenneled shelter dogs. I am interested in further evaluating the use of novel methods in computer science and the field of animal behavior to 1) remove coder biases 2) increase productivity and 3) allow for immediate analysis in real-time for active organizations and shelters.
