Research

The aim is to develop translational tools that can provide accurate and personalized diagnosis and treatment optimization for mental and substance use disorders. This can be achieved by identifying objective markers associated with mental disorders and their treatment outcomes through multimodal data, including electronic health records, brain imaging, genetic, biological, behavioural, cognitive and clinical measurements, and by applying advanced machine learning and statistical algorithms to these data.

Using large-scale data and machine learning techniques, our lab is interested in how lifestyle, environmental, social, cognitive, and genetic factors affect how we age, especially with respect to the interaction between mental and physical health during aging.