Keynote Speakers

Liz Bacon

Abertay University

Professor Liz Bacon FRSE, CEng, CSci, CITP, FBCS, FIScT is Principal and Vice-Chancellor of Abertay University and a Professor of Computer Science with a PhD in Artificial Intelligence. She is a Fellow of the Royal Society of Edinburgh, a National Teaching Fellow, and a Principal Fellow of the Higher Education Academy. She is a past President of BCS, The Chartered Institute for IT, and EQANIE (European Quality Assurance Network for Informatics Education), a past Trustee and Director of Bletchley Park Trust, and a past Chair of CPHC (Council of Professors and Heads of Computing) Committee, and in 2015 was voted the 35th Most Influential Woman in UK IT. Professor Bacon is a worldwide speaker on a range of topics such as the fourth industrial revolution and improving diversity and participation in STEM, particularly among women and people from disadvantaged backgrounds.

Keynote Title: Reimagining Higher Education for a Future Shaped by AI

Abstract: Artificial intelligence is rapidly shifting from supportive tools to autonomous systems that reshape how knowledge is created, evaluated and applied. This talk explores what that transformation means for universities as AI becomes embedded across every profession, accelerates skills change, challenges trust and security, and alters how humans think and make decisions. Alongside these broader shifts, we examine how students are already incorporating AI into their learning, and how universities must adapt their educational practices to remain effective and credible. Looking ahead, the session asks how universities can stay relevant in the future, and what it will take to redesign curriculum, assessment, digital capability and ethical literacy to create AI‑enhanced environments that genuinely prepare graduates for an intelligent world.

Vittorio Ferrari

Meta

Vittorio Ferrari is a Principal Research Scientist at Meta, working on realistic avatars for next-gen communication on wearable devices. In 2023-2025 he was the Director of Science at Synthesia, where he led R&D groups developing cutting-edge generative AI technology. Previously he built and led multiple research groups on computer vision and machine learning at Google (Principal Scientist), the University of Edinburgh (Full Professor), and ETH Zurich (Assistant Professor). He has co-authored over 160 scientific papers and won the best paper award at the European Conference in Computer Vision in 2012 for his work on large-scale segmentation. He received the prestigious ERC Starting Grant, also in 2012. He led the creation of Open Images, one of the most widely adopted computer vision datasets worldwide. While at Google his groups contributed technology to several major products (with launches e.g. on the Pixel phone, Google Photos, Google Lens). He was a Program Chair for ECCV 2018 and a General Chair for ECCV 2020. He is an Associate Editor of IEEE Pattern Analysis and Machine Intelligence, and formerly of the International Journal of Computer Vision. His recent research interests are in Generative Video, 3D Deep Learning, and Vision+Language models.

Keynote Title: Foundation models for avatar generation

Abstract: Foundation models have emerged as a powerful paradigm across machine learning. The central idea is to pretrain a large model, typically transformer-based, on vast amounts of diverse data without explicit supervision to learn general-purpose representations of an entire domain. These representations can then be adapted to new tasks with relatively little data, enabling strong performance by leveraging knowledge acquired during pretraining. This approach has driven remarkable advances in several areas such as large language models, multimodal vision-language models, speech recognition and generation, protein structure prediction, and image synthesis. In this talk, I will present recent progress in applying the foundation model paradigm to the generation of realistic human avatars. Using examples from Meta and Synthesia spanning both 2D and 3D avatar generation, I will discuss how large-scale pretraining is opening the door to more realistic, expressive, and personalized digital humans.

Alejandro F Frangi

University of Manchester

Prof Alejandro Frangi is the Bicentenary Turing Chair in Computational Medicine at the University of Manchester and the Royal Academy of Engineering Chair in Emerging Technologies. He leads the UK CEiRSI Centre of Excellence on In Silico Regulatory Science and Innovation and is a Fellow of IEEE, SPIE, and MICCAI. With over 330 journal publications, his work focuses on precision computational medicine and digital twins for medical devices. He is also a co-founder of adsilico Ltd and OculomeX Health Ltd.

Keynote Title: Hippocrates Meets Turing: Digital twins for in silico trials: what works, what breaks, what’s next

Abstract: In silico trials powered by credible digital twins are reshaping medical product evidence, enabling faster, safer, and more affordable innovation by shifting human studies towards confirmatory roles. This talk distils general principles for making this shift work at scale: defining clear contexts of use; building end-to-end pipelines from data curation to anatomy/physiology/device modelling; and rigorously managing verification, validation, and uncertainty quantification to establish model credibility. We will outline how to design proportionate, risk-informed evidence strategies across the product lifecycle, integrate real-world data with physics- and biology-based models (including AI), and operationalise virtual cohorts that capture lifestyle, physiological, and operational envelopes. We will also discuss what breaks—limits of generalisability, failure modes in complex anatomy/physiology couplings, credibility gaps, and socio-technical barriers—and how to mitigate them through standards, best practices, and regulatory “airlock” co-creation. Grounded by brief exemplars from cardiovascular devices, the session looks ahead to scalable infrastructure, workforce development, and global frameworks needed to mainstream trustworthy model-informed evidence.

Bashar Nuseibeh

City St George’s, University of London

Bashar Nuseibeh is a Professor and Executive Dean of Science & Technology at City St. George’s, University of London. He serves as Research Pillar Chair of Responsible AI UK (RAi UK), and is an Adjunct Professor Software & Systems at Trinity College Dublin (TCD). Previously he was Chief Scientist of Lero - Ireland’s national software research centre - and a Professor of Computing at The Open University, where he continues his association as Emeritus Professor. He was a Reader in Computing and later a Visiting Professor at Imperial College London, and is an Honorary Professor at University College London (UCL), and a Visiting Professor at University College Dublin (UCD) and the National Institute of Informatics (NII), Japan. Bashar’s research lies at the intersection of software engineering, adaptive systems, and security & privacy, and addresses physical and psycho-social aspects of computing technologies. He is the recipient of a European Research Council (ERC) Advanced Grant on Adaptive Security and Privacy, and contributed to the commercialisation of his patented innovations in industry and business. He is a Fellow of the UK’s Royal Academy of Engineering, the ACM, the BCS, and the IET, and is a Member of Academia Europaea and the Royal Irish Academy. He is the recipient of many awards including a Philip Leverhulme Prize, a Royal Society-Wolfson Merit Award, an ICSE Most Influential Paper Award, and the 2025 IEEE Computer Society’s Harlan D Mills Award for for “long-standing, sustained, and impactful contributions to software engineering practice and research through the development and application of sound theory".

Keynote Title: Responsible Software Engineering of Prosocial Lived Experiences

Abstract: TBD