Simon Ellershaw May Seminar Series
March 12, 2026
We are pleased to welcome Simon Ellershaw, PhD Candidate at University College London (UCL) as part of the UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, who will deliver his talk “Developing Healthcare LLMs: From the NHS to Silicon Valley"
as part of our Seminar Series.
Abstract: This talk links my PhD and my Silicon Valley internship through one theme: what it really takes to build and deploy LLMs in healthcare. I will introduce Foresight England (Foresight E), a national-scale generative foundation model trained from scratch on 54.9 million de-identified longitudinal NHS EHRs to model patient timelines and enable zero-shot prediction across around 40,000 coded medical events. As NHS England has paused data access pending review, I will focus on the core methodology and lessons learned.
I will then switch to my Parexel internship in San Francisco, where I worked in the company’s AI lab on production-focused applications, including pharmacovigilance and protocol de-risking. I will explain how I ended up there, what I worked on, and what I learned, with a candid view of what day-to-day life and work in the Bay Area actually looks like. I will also reflect on how the recent generative AI boom has reshaped the problems teams like ours choose to tackle and the way this work gets built, evaluated, and shipped.
Seminar Series Event: “Developing Healthcare LLMs: From the NHS to Silicon Valley"
Date and Time:
Wednesday 27 May 2026, 15:00 – 16.00 hrs (BST)
Location: Judy Dunn, SGDP Building, Denmark Hill Campus
Attendance:
Mandatory for all DRIVE-Health students; a calendar invitation has already been sent.
Registration:
Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk
to let us know if you would like to attend.
Biography
Simon Ellershaw is a PhD Candidate at University College London (UCL) as part of the UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, supervised by Prof Richard Dobson and Dr Anoop Shah. His research spans LLM-based generation of hospital discharge summaries, national-scale pre-training of generative models on 57 million electronic health records, and post-training using real-world patient outcomes as verifiable reinforcement-learning rewards. Alongside his PhD, he interned at Parexel AI Labs and now works part-time as an NLP Engineer, developing and deploying production LLM/NLP systems, including applications in pharmacovigilance and quality assurance.
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We are looking forward to welcoming Professor Honghan Wu, Professor of Health Informatics and AI at the University of Glasgow, who will deliver his talk “Large language model and Radiology: how to facilitate human and AI collaboration? " as part of our Seminar Series. Abstract: In this upcoming talk, Professor Honghan Wu explores the essential shift from viewing AI as a potential replacement for radiologists to recognizing it as a critical collaborative partner. Moving beyond basic tasks like detection and triage, the presentation highlights how AI can address practical clinical "pain points," such as reducing automated protocoling time by up to 60% and decreasing the time spent communicating with providers and patients by 30%. Professor Wu will present recent research on using knowledge-retrieval and Large Language Models for clinical report error correction and generation. The session concludes with an examination of the real-world deployment lifecycle, discussing the challenges of monitoring the over 700 FDA-cleared radiology AI devices currently in practice Seminar Series Event : “Large language model and Radiology: how to facilitate human and AI collaboration?" Date and Time: Thursday 25 November 2026, 15:00 – 16.00 hrs (GMT) Location: Venue to be confirmed. Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Biography Honghan Wu is a Professor of Health Informatics and AI, based in the School of Health and Wellbeing of the University of Glasgow, where he leads the research theme of data science and AI. Prof Wu is a co-director of Health Data Research Scotland. He also is an honorary professor at Hong Kong University, an honorary associate professor at Institute of Health Informatics, UCL, and a former Turing Fellow of The Alan Turing Institute, UK's national institute for data science and artificial intelligence. Prof Wu holds a PhD in Computing Science. His current research focuses on machine learning, natural language processing, knowledge graph and their applications in medicine.
We are looking forward to welcoming Dr. Bettina Moltrecht and Thomas Wood to introduce Harmony Meta , a groundbreaking platform developed over the past year to bridge the gap between disparate study catalogues and registers. While traditional data discovery relies on exact keyword matching, Harmony Meta utilizes Large Language Models and vector indexing to allow for semantic searching across 5.5 million variables . Abstract: This session will demonstrate how researchers can now locate longitudinal data using approximate synonyms—for instance, a search for "dyslexia" will successfully retrieve variables related to "difficulty reading." The platform indexes nearly every major longitudinal study ever conducted in the UK, including the Millennium Cohort Study , the 1970 British Cohort Study , and Born in Bradford . The presenters will discuss the technical backend of converting millions of variables into vectors and the practical implications for harmonizing data across different cohorts to identify population mental health trends. Try the Tool: https://harmonydata.ac.uk/search Seminar Series Event : " Harmony Meta: Using AI to Unlock 5.5 Million Variables in UK Longitudinal Studies" Date and Time: Thursday 24 September 2026, 15:00 – 16.00 (BST) Location: Venue to be confirmed. Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Biographies Dr. Bettina Moltrecht Dr. Bettina Moltrecht is a mental health researcher based at University College London (UCL) and Anna Freud a UK-based mental health charity for children and families. Bettina combines a clinical, tech and research background, and has been co-leading the Harmony project with the aim to enhance population mental health research. Bettina is co-founder of UCL's Digital Mental Health Hub, and is co-investigator on various clinical trials to evaluate mental health interventions in the NHS. Thomas Wood Thomas Wood is the founder of Fast Data Science and the lead developer for the Harmony Meta backend. He holds a Master’s in Physics from Durham University and a Master’s in Computer Speech, Text and Internet Technology from the University of Cambridge. With over a decade of experience in machine learning and NLP, Thomas has consulted for the NHS, Tesco, and Boehringer Ingelheim. He also works as an expert witness and is working on NLP solutions for clinical trials, and generative AI solutions for legal question answering. Note on Funding and Partners: Harmony Meta was funded by the ESRC and developed in collaboration with Population Research UK (PRUK), the UCL Centre for Longitudinal Studies, DATAMIND UK, The Alan Turing Institute, and UK Research and Innovation.
