Dear Colleagues, The 7th Annual UCL NeuroAI Conference will take place on Wednesday 11 November 2026 at the Kennedy Lecture Theatre, UCL Great Ormond Street Institute of Child Health, London. The event will feature leading speakers at the cutting edge of machine learning and neuroscience. The UCL NeuroAI initiative aims to be a central hub where researchers working in neuroscience, AI, machine learning, and related fields can interact and stay updated on the latest advancements in these intersecting areas. Our annual conference is an important opportunity for these communities to gather, make new connections, and benefit from insights in one another’s fields. *Keynote speakers* We are privileged to have a distinguished line-up of speakers and experts confirmed to date. Wolfgang Maass, Technische Universität Graz Agostina Palmigiano, Gatsby Computational Neuroscience Unit Bernardo Sabatini, Harvard Medical School Nicolas Skatchkovsky, Francis Crick Institute Eleni Vasilaki, University of Sheffield Ellie Pavlik, Brown University *Registration * Registration is required and the conference ticket is £5 but if the cost is a barrier, please email events@ucl.ac.uk for a complimentary ticket. Please register here <https://www.bloomsburytheatre.com/event/2026/11/neuroai-conference-2026>. *Poster and talks - Submissions are now open!* This year we will also be accepting abstract submissions for posters, short lightning presentations (3-4 mins), as well as longer submitted talks (15 mins) as part of the event. The deadline to submit your abstract for these is *Friday 16 October at 12pm*. Please remember to book your conference place as well as completing the abstract registration form if you would like to present. Submit your poster or talk abstract now here <https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=_oivH5ipW0yTySEKEdm...>. *Sponsorship* We are immensely grateful for the support from the Sainsbury Wellcome Centre, Callosum Technologies and Google DeepMind. *About UCL NeuroAI* The last decade has seen phenomenal advances in the fields of machine learning (e.g. deep learning, reinforcement learning, and AI). While these changes have already had considerable impact on most areas of science they hold a particular resonance for neuroscience. Crucially, AI shares a common lineage with neuroscience and, fundamentally, machine learning and the brain employ similar computations to process and compress information. For these reasons AI provides a means to emulate neural functions and the circuits supporting them, providing insights to aid our understanding of the brain and cognition. Equally, AI tools provide a means to discover, segment, and track distinct neural and behavioural states, yielding more efficient experiments and accelerating the pace of discovery. In turn, this understanding feeds back into the design of more effective AI architectures and models. Essentially, AI problems posed in neuroscience both require and inspire further advances in AI. UCL NeuroAI has been set up to provide a forum where researchers in these areas can meet, exchange ideas, and move both fields forward. -- ----------------------------------------------------- Padraig Gleeson http://openneuroai.org Room 321, Anatomy Building Department of Neuroscience, Physiology & Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson@ucl.ac.uk -----------------------------------------------------