EPSRC DRIVE-Health CDT Summer Symposium

May 6, 2024
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Join our DRIVE-Health community for an exciting in-person event where we dive into the world of Generative AI and how it is shaping the future of healthcare. Our theme this year is ‘From Generative AI to Generating Impact,’ which aims to explore the ways in which developing and deploying AI in the real-world influences healthcare outcomes and advances medical research. From cutting-edge technologies to real-world applications, this symposium will explore the latest trends and innovations in the field. Meet students from across KCL faculties, network with industry partners, exchange ideas, and gain valuable insights to drive results in your own projects. Don't miss out on this opportunity to be part of the conversation!


Registrations have now close. To be added to the waiting list, please email drivecdt@kcl.ac.uk


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.


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11 & 12 June: Summer Symposium & Partner Showcase

April 28, 2026
Bridging Academia and Industry: Turning Health Data into Health Solutions Please join us for the EPSRC DRIVE‑Health CDT Summer Symposium & Partner Showcase 2026 , a two‑day event dedicated to bridging academia and industry and accelerating the journey from health data research to real‑world solutions. This year’s theme, “Bridging Academia and Industry: Turning Health Data into Health Solutions", brings together our vibrant community of students, King’s academics, industry partners, clinicians and policymakers to explore how collaboration can unlock new insights, innovation and impact across health and care. Event details 📅 11 & 12 June 2026 📍 Science Gallery London, Guy’s Campus, King’s College London, Great Maze Pond, London SE1 9GU Timings: ⏰ 10:00–16:00 each day ☕ Refreshments available from 09:30 👉 Please be seated by 09:50 for a prompt 10:00 start Please secure your place here: Register Now Programme highlights KEYNOTE ✨ Dr Luis Garcia‑Gancedo , Executive Director & Head of Digital Medicine – Respiratory, Immunology & Inflammation, GSK INTERACTIVE DEBATE ✨ Student‑led interactive debate exploring AI within the context of the event theme: “Bridging Academia and Industry: Turning Health Data into Health Solutions.” PANEL DISCUSSION & POSTER JUDGING ✨ “What does industry actually need from health data PhDs - and how can industry partner with academia for maximum impact?” Panelists confirmed so far: Dr Laura Acqualagna , Director of AI/ML Engineering, GSK R&D Dr Chris Callaghan , Consultant Transplant Surgeon, Guy’s Hospital Dr Nina Sesto , CEO & Co‑Founder, MEGI Health Dr Srinivasan Vairavan , Director of Data Science & Digital Health, JNJ Innovative Medicine R&D, and Visiting Adjunct Faculty, King’s College London Dr Nicolas Huber , Director, King’s Innovation Catalyst PLUS ✨ Student lightning talks (across both days) ✨ 3‑minute Student Spotlight Slides (across both days) ✨ Poster showcase & networking session (Friday) ✨ Prizes for outstanding contributions (Friday) Please secure your place here: Register Now If you are no longer able to attend the event, please email drive-health-cdt@kcl.ac.uk so that we can reallocate to our waiting list.

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.