Roshan Rane

Roshan’s Ph.D. research lies at the crossroads of computer science and mental health research. He analyses large population neuroscience databases that include brain MRIs, mental health reports, and ecological assessments (smartphone & smartwatch data). Specifically, Roshan develops explainable machine learning (xAI) methods that can be trained on brain MRIs and discover potential biomarkers of mental health phenotypes such as addiction. Mental health problems such as depression, anxiety, and addiction disorders emerge from an interaction between our brains (physiology and psyche) and our environment (demands of life and the structures of our society). Therefore, Roshan aims to develop xAI methods that can predict mental health phenotypes while accounting for the mediating and confounding influence of the environment and society.