Fiona Coutts is a postdoctoral researcher in the Department of Psychosis Studies in the field of transdiagnostic machine learning in mental health. Her main focus is on building machine learning models to predict poor outcomes and guide treatment decisions in mental health disorders such as psychosis, depression, and bipolar disorder.

Fiona studied at the University of Cambridge for her undergraduate degree, graduating with an MA in Natural Sciences in 2017. She then joined King’s College London, where she undertook an MSc in Genes, Environment and Development in Psychology and Psychiatry, which was awarded in 2018. Following this she was awarded a 1+3-year MRC PhD studentship in Neurodevelopmental Disorders at King’s College London: during the course of this studentship she received an MRes in Neurodevelopmental Disorders in 2019 and completed her PhD in 2023.

Supervised by Professor Philip McGuire and Professor Nikolaos Koutsouleris, Fiona’s PhD focussed on using supervised machine learning methods to predict outcomes in psychosis populations using clinical, environmental, cognitive and genetic data from large multisite studies. She now hopes to continue and expand upon this work in her current role by applying these models to other mental health populations.

 

Research Interests: 

• Multimodal prediction modelling
• Artificial Intelligence
• Early intervention in mental illness
• Treatment response in mental health disorders
• Mechanistic overlap and comorbidity of mental health disorders

Research Groups: 

• Artificial Intelligence in Mental Health (AIM) lab

Expertise and Public Engagement:

Member of the Centre for Neurodevelopmental Disorders Public Engagement Committee (2022-2023)