AIMSA 2026

KEYNOTE SPEAKERS

Prof. Steve Furber
Professor Emeritus

Organization: University of Manchester, Department of Computer Science

Lecture title: The SpiNNaker Project

Abstract: The SpiNNaker project at the University of Manchester delivered a machine incorporating over a million ARM processor cores with a communications fabric optimised for large-scale brain modelling applications running in biological real time. The machine supported an open neuromorphic computing service under the auspices of the EU Flagship Human Brain Project (HBP) continuously from April 2016, and was for several years the world’s largest neuromorphic computing platform, a position only recently ceded to Intel’s Hala Point. A second generation SpiNNaker2 system was co-developed within the HBP by the University of Manchester and the Technical University of Dresden incorporating lessons learnt from the SpiNNaker1 service. This year TU Dresden has built a 5 million core SpiNNaker2 system for data centre scale neuromorphic and AI applications. SpiNNaker2 is being actively commercialised by SpiNNcloud Systems GmbH with a focus on deploying mainstream AI and hybrid models, which is especially important following recent algorithmic breakthroughs in mainstream AI whose full potential is hard to realise without brain-inspired architectures.

ShortBio: Steve Furber CBE FRS FREng is Professor Emeritus in the Department of Computer Science at the University of Manchester, UK. After completing a BA in mathematics and a PhD in aerodynamics at the University of Cambridge, UK, he spent the 1980s at Acorn Computers, where he was a principal designer of the BBC Microcomputer and the ARM 32-bit RISC microprocessor. Over 300 billion ARM-powered chips have since been manufactured, powering much of the world's mobile and embedded computing. He moved to the ICL Chair of Computer Engineering at Manchester in 1990 where he led research into asynchronous and low-power systems and, more recently, neural systems engineering, where the SpiNNaker project delivered a computer incorporating a million ARM processors optimised for brain modelling applications.

Dr Ann Thanaraj

Organization: Teesside University

Lecture title: The AI-resilient learner: beyond AI literacy to responsible agency

Abstract: As generative and agentic AI reshape learning, higher education must move beyond AI literacy to cultivate resilient graduates capable of responsible judgement, accountability and professional agency.
The central challenge is no longer teaching students how to use AI, but ensuring they retain the capacity to question it, justify its use, and remain accountable for decisions made alongside increasingly autonomous systems. This presentation introduces the concept of the AI-resilient learner, proposing a developmental pathway from AI literacy, through AI skills, to responsible agency.
Students no longer simply need AI literacy; they require epistemic resilience, philosophical reasoning, ethical judgement, and responsible professional practice to navigate an AI-enabled world with discernment and accountability. The talk argues that resilience is characterised by epistemic responsibility: the capacity to question, justify and remain accountable for knowledge, decisions and actions undertaken in partnership with AI.
Rather than treating AI ethics as a standalone topic, the session demonstrates how responsible agency can be embedded across curriculum design, pedagogy and assessment. Drawing on the implementation of a university-wide AI Resilient Learner programme for more than 22,000 undergraduate students, alongside a pioneering postgraduate Philosophy of AI and Responsible Use module engaging over 4,000 postgraduate students, the presentation offers a practical institutional framework for embedding responsible AI education at scale.
Together, these initiatives demonstrate how universities can move beyond teaching AI tools to cultivating graduates who think critically, exercise sound judgement, and act responsibly in an AI-enabled society. The future of higher education is not simply producing AI-capable graduates, but developing professionals who exercise wisdom, responsibility and human judgement in partnership with AI.

ShortBio:Dr Ann Thanaraj is Associate Professor and Head of Digital and AI Innovations, where she leads institutional strategy for AI-enabled digital transformation in higher education. An internationally recognised academic leader, she works at the intersection of artificial intelligence, education, law and organisational change, supporting universities, government, industry and the legal sector to develop future-ready strategies that translate digital innovation into meaningful educational, social and economic impact.
A barrister by background, Ann is widely recognised for pioneering Digital Lawyering, a nationally influential body of scholarship on digital capability and curriculum innovation that has been cited in the House of Lords. Her current work explores responsible AI, epistemic resilience and the development of the AI-resilient learner, informing institution-wide approaches to curriculum, assessment and professional practice.
Ann holds visiting professorships at UK universities and advises international boards and parliamentary stakeholders on AI and digital transformation. She is a Principal Fellow of Advance HE and a National Teaching Fellow in recognition of her sustained contributions to research, policy and educational leadership. She has authored more than 50 peer-reviewed publications and three books, with expertise spanning law, digital leadership, and education.
Ann co-leads Teesside University's AI strategy, driving institution-wide implementation, governance and policy while addressing the fundamental philosophical and pedagogical questions raised by artificial intelligence. Her work explores what it means to be a university in the age of AI and how higher education can cultivate graduates who are intellectually resilient, ethically grounded and capable of exercising responsible agency in an AI-enabled world.
She is the architect of Teesside's university-wide AI Resilient Learner programme, supporting more than 22,000 undergraduate students, and the creator of the postgraduate Philosophy of AI and Responsible Use module for over 4,000 postgraduate learners. Together, these initiatives provide a coherent educational framework that moves beyond AI literacy to develop epistemic resilience, critical judgement and responsible professional practice at scale.