Rate My Professor Dan Joyce

University of Liverpool

Computer Science Health Science Medicine Psychology Psychiatry & Psychology Artificial Intelligence Machine Learning Neuroscience Computing in Mathematics, Natural Science, Engineering and Medicine

5.0

1 review · out of 5

Rate Dan

Is this you? Claim this profile

Ratings & reviews

5.05/4/2026

Inspires curiosity and a thirst for knowledge.

Taught by or worked with Dan ?

Add your rating. It takes about 30 seconds.

About Dan

Professor Dan Joyce serves as Professor of Connected Mental Health in the Department of Primary Care and Mental Health within the Institute of Population Health at the University of Liverpool. He is concurrently a consultant psychiatrist at Mersey Care NHS Foundation Trust. Joyce's academic background combines expertise in computer science and medicine: he earned a BSc in Computer Science (1995) and a PhD in Artificial Intelligence (2001) from the University of Southampton, an MBBS from King's College London (2010), and membership of the Royal College of Psychiatrists (MRCPsych, 2015). His career trajectory reflects a unique integration of computational methods with clinical psychiatry, transitioning from AI research to medical practice and back to data-driven mental health innovation.

Joyce's research specializations center on leveraging data-driven technologies to advance understanding and management of mental illness. He employs statistical and machine-learning methods to generate actionable insights, focusing on transdiagnostic phenotyping from clinical data, unobtrusive monitoring of health states through wearable and passive sensing technologies, and alignment of clinical decision-making with artificial intelligence systems. Key areas include natural language processing of electronic health records to identify phenotypes such as difficult-to-treat depression, uncertainty quantification in predictive algorithms, interpretable machine learning techniques like decision trees, analysis of multivariate time-series data from experience sampling and sensors, and socio-technical strategies to address biases in data and algorithms, particularly for underrepresented groups. He leads active projects on synthetic data generation, clinical algorithm interpretability, and beyond-anomaly-detection analysis of time-series data. Joyce holds prominent appointments, including Co-Director of the Mental Health Research for Innovation Centre (M-RIC), where he oversees work packages on Innovative Therapies for Mood Disorders and the Mental Health Avatar; Mental Health Theme Lead at the Civic Health Innovation Labs (CHIL); and NHS Lead for Mersey Care in the Liverpool Interdisciplinary Neuroscience Centre. His influential publications include 'Explainable artificial intelligence for mental health through transparency and interpretability for understandability' (npj Digital Medicine, 2023), 'A participatory initiative to include LGBT+ voices in AI for mental health' (Nature Medicine, 2023), 'CHRONOSIG: Digital Triage for Secondary Mental Healthcare using Natural Language Processing' (medRxiv, 2021), 'Realising stratified psychiatry using multidimensional signatures and trajectories' (Journal of Translational Medicine, 2017), and contributions to 'Research Methods in Mental Health: A Comprehensive Guide' (2025). With over 2,450 citations, his work significantly impacts stratified psychiatry and AI applications in mental healthcare.