Cynthia H.Y. Fu

Professor Cynthia H.Y. Fu is a leading researcher in the Department of Psychology & Human Development at the University of East London's School of Childhood and Social Care. She serves as an Honorary Consultant Psychiatrist at the South London and Maudsley NHS Foundation Trust and holds a Visiting Professor position at the Centre for Affective Disorders, King's College London.

Her research focuses on identifying brain regions affected by depression and how they change with various treatments including talking therapies, antidepressant medication, and neurostimulation techniques like transcranial direct current stimulation (tDCS). Professor Fu pioneered work demonstrating that neural activation patterns during sad facial processing can accurately diagnose depression in individual patients and predict treatment response. Her research has direct translational potential in developing biomarkers for diagnosis and prognosis based on brain imaging.

Professor Fu's work spans multiple disciplines including affective neuroscience, computational psychiatry, and neuromodulation. Her recent publications reveal strong trends in applying machine learning to neuroimaging data for depression classification, investigating home-based tDCS treatment protocols, and exploring the relationship between physiological markers and psychological states in real-world contexts like driving and commuting.

• British Association for Psychopharmacology Award
• National Alliance for Research in Schizophrenia and Depression (Brain & Behavior Research Foundation) Award

Professor Fu has secured significant research funding from major organizations including the Medical Research Council, Wellcome Trust, GlaxoSmithKline, and Eli Lilly. Her work regularly appears in top-tier journals and is consistently cited among the most influential publications in psychiatry. She leads research investigating how brain responses can predict individual treatment responses, potentially enabling personalized depression treatment approaches.

Her laboratory focuses on multimodal neuroimaging approaches combined with machine learning to identify neural signatures of depression and treatment response. Current projects include home-based tDCS treatment protocols with remote supervision, biomarker development for predicting antidepressant response, and computational approaches to understanding stress responses in everyday contexts.