Invited Speaker: John Vardakis, Co-Founder & CSO at Science Card

May 23, 2024

We are thrilled to invite John Vardakis to speak at our EPSRC DRIVE-Health CDT's summer symposium next month. John joins us from Science Card to talk about "Exploring the Frontier: The future of GenAI Investments and Collaborations in Industry and Academia."

John Vardakis, PhD, has a diverse work experience, primarily in the field of scientific research. John is currently serving as the Head of Science Card Investment Group at Science Card, where they are involved in innovative banking. Previously, they worked as a Research Scientist at the University of Glasgow, where they focused on simulation-driven microelectromechanical systems design. John also worked as a Research Scientist at INSERM, investigating tumor mechanics and vascular fractality quantification. At the Center for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), they conducted research in cardiovascular and cerebrovascular biomechanics. Their work at UCL involved computational modeling of dementia and image-guided neurosurgery for epilepsy. John completed their DPhil in Biomedical Engineering at the University of Oxford, where their research focused on fluid transport in the brain. John also gained experience in the fields of vascular diagnosis and market research at the University of Heidelberg and P2i, respectively. Additionally, they worked as a Mechanical Engineer at Enactus and completed a placement at King's College London's Centre for Robotics Research.


John Vardakis, PhD has a strong educational background in engineering and innovation. John obtained their Bachelor of Engineering (BEng) degree in Mechanical Engineering from King's College London in the years 2005 to 2008. John then pursued further education at the University of Oxford, where they completed the Centre for Doctoral Training in Healthcare Innovation from 2009 to 2010. Following this, they earned a Doctor of Philosophy (PhD) degree in Biomedical/Medical Engineering from the University of Oxford from 2010 to 2014. During their time at Oxford, they also pursued a diploma in Strategy & Innovation (Science Innovation Plus programme) from Saïd Business School, University of Oxford, from 2011 to 2012.


In addition to their academic degrees, John Vardakis has obtained additional certifications. In December 2010, they received a Mathwork Training Certificate for completing the "Deploying MATLAB Based Applications - .NET Edition" course. John also obtained another Mathwork Training Certificate in December 2010 for completing the "MATLAB Programming Techniques" course.


Registration is required, please email drivecdt@kcl.ac.uk for further event details.


Our annual Symposium is a one-day face-to-face event for all DRIVE-Health students, academic supervisors, stakeholders and partners.  Our aim is to discuss translating scientific and technological innovations in AI and data science, from research to clinical practice and commercial enterprise.


The symposium will feature keynote talks, panel discussions, and poster presentations showcasing cutting-edge research and successful case studies. We will also celebrate our coming together with networking drinks at the end of the symposium.


The EPSRC DRIVE-Health Centre for Doctoral Training is training the next generation of PhD health data scientists to become the innovation leaders of tomorrow. Our students work within an active NHS environment, and develop new models of data-driven care, whilst leveraging significant recent investment and infrastructure in Health Data Research within the UK.


By registering for this event, you give consent to provide your name, e-mail address and registration information with King's College London for the purposes of managing the EPSRC DRIVE-Health CDT's Summer Symposium. Your personal data will be managed by those organisations and by Eventbrite according to their published privacy policies.



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Prof Honghan Wu June Seminar Series

March 12, 2026
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 June 2026, 15:00 – 16.00 hrs (BST) Location: Large Committee Room, Hodgkin Building, Guy's 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 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.

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.