Chris Tomlinson

Chris Tomlinson


Senior Research Fellow in Health Data Science

UCL Institute of Health Informatics

Health Data Research UK


Chris is a senior research fellow in health data science and clinical PhD student at UCL, on track to submit his thesis on informatics and AI-based approaches for scalable phenotyping of electronic health records (EHR), in early 2024.

He has over a decade of experience in healthcare, spanning physiological research and clinical medicine, as well as quantitative methods in epidemiology and machine learning. His work has been featured in top medical journals (Nature Medicine, Circulation, BMJ, Lancet Digital Health) and informed policy at home and abroad.

He is excited about the ability of artificial intelligence to flexibly integrate, structure and summarise insights from both traditional knowledge repositories and observational data, to scalably advance our understanding of health and disease, and enable us to address the fundamental challenges of precision medicine: diagnosis, prognosis and treatment response.


  • Phenomics: Defining clinically-relevant phenotypes at scale to unlock healthcare data for research & patient benefit
  • Representation learning: Harnessing Large Language Models (LLMs) and Graph Neural Networks (GNNs) to build multi-modal, predictive representations that codify both domain knowledge and data-driven insights
  • Uncertainty quantification: for clinical evaluation and scientific discovery, through assessing robustness to distributional shift and performance in inductive learning settings
  • Causal inference: for evidence generation from observational data and to learn better representations
  • Real-world evidence: I prioritise working with routinely-collected healthcare data to ensure my research is of direct relevance to patients, clinicians and policymakers


  • PhD Candidate: Artificial Intelligence enabled healthcare 2021-2024
    UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, UCL Institute of Health Informatics
  • MRes: Artificial Intelligence enabled healthcare 2021
    UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, UCL Institute of Health Informatics
  • MRCA: Primary Fellowship of the Royal College of Anaesthetists 2018
    Royal College of Anaesthetists
  • DMCC: Diploma in Medical Care of Catastrophes 2016
    The Worshipful Society of Apothecaries of London
  • MBBS: Bachelor of Medicine & Surgery 2014
    University College London
  • BSc: Bachelor of Medical Sciences with Physiology (1st Class Hons) 2011
    University College London



Chris enjoys productive collaborations spanning computer science, health informatics and clinical medicine across UCL institutions, other universities within the UK, and abroad, as well as organisations such as Health Data Research UK, British Heart Foundation Data Science Centre, The Alan Turing Institute and Wellcome Trust and industry partners such as GSK, Databricks and AWS.

He strongly believes in the value of multidisciplinary collaboration for delivering responsible innovation and impacts, particularly in complex areas such as healthcare and biomedicine, as well as relishing the learning opportunities that this provides.

This ethos is reflected in a wide range of co-authors, as visualised in the interactive network diagram below:

Featured Presentations


Should you be interested, you can follow my latest updates on Twitter @tomlincr: