My research focusses on building machine learning models to predict poor outcomes and guide treatment decisions in mental health disorders such as psychosis, depression, and bipolar disorder.

During my PhD I focused on using supervised machine learning methods to predict outcomes in psychosis populations using clinical, environmental, cognitive and genetic data from large multisite studies. In my current postdoctoral research role I am continuing and expanding upon this work by applying these models to other mental health populations.