Professor Louise Thomas

My research career has focused on understanding why individuals with similar weight and height can experience very different risks of metabolic disease. This question has shaped more than three decades of work developing and applying advanced magnetic resonance (MR) imaging and spectroscopy techniques to characterise human body composition with precision. My contributions include whole‑body MRI protocols, quantitative phenotyping methods, and deep‑learning approaches that now enable automated analysis at population scale.

I joined the University of Westminster in 2014 and have since helped establish and lead two major initiatives: the Research Centre for Optimal Health (ReCOH) and the Health Data Sciences Research Group. In 2022, I became Director of Research and Knowledge Exchange for the School of Life Sciences, where I oversee research strategy, support academic career development, and shape the School’s contribution to institutional priorities.

My work is grounded in interdisciplinary collaboration, spanning metabolic imaging, data science, quantum biology, and industrial innovation, and is driven by a commitment to improving health through rigorous, accessible, and scalable scientific methods.

My research focuses on developing and applying MR‑based techniques for detailed phenotyping of human tissues and organs. Early work centred on mapping adiposity and ectopic fat in obesity and non‑alcoholic fatty liver disease (NAFLD), and has since expanded to encompass precision phenotyping across the whole body. This includes the development of cost‑effective alternatives to MRI, such as biomarker‑based indices and algorithmic proxies, to improve accessibility and scalability.

A major strand of my research is biobank‑scale imaging, particularly the UK Biobank imaging study, one of the world’s largest population imaging initiatives. I have contributed to the development of automated pipelines and deep‑learning segmentation methods that enable the extraction of organ volumes, tissue composition, and metabolic phenotypes from tens of thousands of MRI scans. These tools make it possible to link imaging features to genetics, biomarkers, lifestyle factors, and longitudinal health outcomes, providing new insights into metabolic risk, ageing, and disease trajectories. My work in this area has helped establish reproducible, scalable approaches that are now widely used across the research community.

My research also examines metabolic health and disease mechanisms, with a particular focus on ectopic fat, muscle quality, liver and pancreatic composition, and the heterogeneity of obesity. By combining imaging with biochemical, clinical, and lifestyle data, I aim to identify early markers of disease and understand the pathways that drive metabolic dysfunction.

A further dimension of my work involves translational imaging and industrial collaboration. I have partnered with organisations including Calico LLC, Perspectum Diagnostics, Novo Nordiak, AMRA, Antidote LDN, contributing to projects that range from algorithm development to the application of imaging biomarkers in clinical and commercial settings. These collaborations ensure that methodological advances translate into real‑world impact.

I also maintain an active interest in quantum biology and bioenergetics, through the Guy Foundation Quantum Biology and Bioenergetics Laboratory which explores fundamental mechanisms that underpin metabolic processes. 

Across all strands, my research is driven by a commitment to methodological rigour, interdisciplinary collaboration, and the development of tools that improve understanding of metabolic health at both individual and population levels.

For details of all my research outputs, visit my WestminsterResearch profile.