My research is focused on how we make the decisions we do. More specifically, I'm interested in how people are able to integrate information about complex environments in order to guide their actions, with a particular emphasis on how people learn from feedback. As well, I want to better understand how stress both harms and helps our ability to make decisions. This is because I think that a great way to understand a system (in this case the brain-behaviour relationship) is by seeing what happens in situations when the system is taxed or strained. 

Currently, my research uses neuroimaging (specifically electroencephalography) in conjunction with computational modelling to understand how decision making and reward learning break down when people are stressed. I have adopted this approach is because computational modelling allows for latent variables to be extracted to compliment behaviour and cognition. I am also interested in how people find their way around their environment (navigational cognition). Some of my previous work has examined the effects of stress on navigation strategy and performance, and the role of reward learning in navigation.

Other than my work on decision making and navigation, I am interested in statistics and have used both frequentist and Bayesian approaches in my research. As well, I am always looking for ways to improve how my data is visualized. Some examples of these interests can be seen on my GitHub ( or on the code section of this website. When I'm not working on my research or analysis, I will likely be coding. I've worked in the following languages: (1) MatLab, (2) R, (3) Python, & (4) HTML. I also have experience using SPSS.