Sam’s research uses machine learning to improve understanding of adult social care. He has trained Large Language Models (LLMs) to capture previously unmeasured needs, such as loneliness, in free-text case records. His work also explores the ethics of AI in public services, evaluating gender bias in LLMs used for social care practice. Sam leads the Data Science group at the Global Observatory of Long-Term Care (GOLTC).

Sam’s background spans both research and over a decade’s experience in public sector roles. Before joining CPEC, he managed a local authority social services team in inner London and worked as a qualified social worker, supporting adults with dementia, physical disabilities, mental health issues, drug and alcohol problems, and histories of offending.

Sam holds an MA (Cantab) in Social and Political Science, an MA with distinction in Social Work from Goldsmiths College. He is also completing a PhD by papers at LSE, focusing on how LLMs can make use of unstructured text data to support social care policy and practice.

Sam enjoys building interactive tools to make research more accessible, such as the European Project Data Explorer. He has also written guides for GOLTC on presenting geospatial data, including Communicating the findings of long-term care research using interactive maps. Committed to reproducible research, Sam shares his code, written primarily in Python, R, and JavaScript, on his GitHub.