Lewis Hotchkiss
What is your field of research?
I’m currently a Research Officer at the Dementias Platform UK Data Portal, where my research focuses on the development and responsible translation of artificial intelligence into real-world practice.
Currently, my work involves building AI models for the differential diagnosis of dementia subtypes using neuroimaging data collected from memory clinics. This also includes exploring the role of 3D MRI synthetic data to address data imbalance issues to improve robustness and generalisability to different subtypes in these models.
Alongside this, I contribute to shaping governance and standards for AI in sensitive health data research. I led the DARE UK funded AI Risk Evaluation Group, which evaluated potential risks of AI models and how these could be mitigated, and I currently lead the UK Synthetic Data Community Group, bringing together trusted research environments across the UK to develop consensus frameworks for synthetic data use.
How did you become interested in the field?
I first became interested in applying AI to health during an internship with the Oxford Protein Informatics Group, where I worked on developing AI models to accelerate drug discovery for Covid-19 treatments. This experience highlighted the real-world potential of data science to address urgent health challenges and inspired me to explore how AI could be applied to more complex, long-term conditions such as dementia. I then gained experience in neuroimaging research, which then led to my position at DPUK.
How did you come to work at Swansea University?
I completed my BSc in Computer Science at Swansea University, where I gained a strong technical foundation. After graduating, I joined Dementias Platform UK within Population Data Science at Swansea. The University’s strong position as a leader in health data science made it a natural place for me to continue my academic and professional journey.
What do you hope to achieve with your research?
My long-term goal is to ensure that AI models move beyond proof-of-concept research and can be safely, responsibly, and effectively deployed in real-world clinical practice. I aim to promote responsible AI development practices that protect patient privacy, mitigate bias, enhance transparency, and ultimately ensure that AI is developed for the public good.
What practical applications could your research have?
My research is designed to make sure that AI tools used in health data research are safe, fair, and trustworthy. This involves protecting people’s data, reducing bias, and ensuring that AI models can work reliably across different patient groups. The governance frameworks that I have helped to develop will hopefully inform how trusted research environments across the UK manage and evaluate new technologies like AI and synthetic data, ensuring that innovations are translated into practice in a safe and equitable way.
What is next for your research?
The next phase of my research is focused on expanding the adoption of synthetic data across the UK data research landscape. Synthetic data has the potential to transform how researchers access and use health data by supporting training, teaching, data discovery, and federated infrastructure. I have just received further funding to support this which will include engagement with the NHS, Information Commissioner’s Office, government departments, and international partners through workshops and training. These collaborations aim to refine guidance, develop recommendations, and ensure a coordinated national approach to the responsible use of synthetic data.
Career History
I gained my BSc in Computer Science from Swansea University, where I first developed my passion for applying AI to health. During my undergraduate studies, I completed an internship at the Oxford Protein Informatics Group, where I contributed to AI models supporting Covid-19 drug discovery. Following graduation, I joined Dementias Platform UK as a Research Officer within Population Data Science at Swansea University.
I am currently pursuing a PhD in Population Data Science at Swansea, with a focus on AI, neuroimaging, and synthetic data in dementia research.