Connectionists: University College London NeuroAI Annual Conference - 5th Nov - in person and online

[Padraig Gleeson]

Dear Colleagues,

The 6th annual UCL NeuroAI Conference will take place on Wednesday 5 
November 2025 at UCL Great Ormond Street Institute of Child Health in 
London. The event features 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.

     Leena Chennuru Vankadara (Gatsby Computational Neuroscience Unit, UCL)
     Netta Cohen (University of Leeds)
     Nathaniel Daw (Princeton University)
     Quentin Huys (Institute of Neurology, UCL)
     Kenneth Harris (Institute of Neurology, UCL)
     Armin Lak (University of Oxford)

All information including how to register can be found here 
<https://www.ucl.ac.uk/research/domains/neuroscience/ucl-neuroai>. 
Spaces are limited so we recommend booking asap to avoid disappointment. 
Registration fee for the conference is £5. If you are unable to pay for 
any reason, please contact neuroaievents at ucl.ac.uk.

*Poster and lightning talks - Submissions are now open!*

This year we will also be accepting abstract submissions for posters or 
a short lightning presentation as part of the event. The deadline to 
submit your abstract (200 words) is *Wednesday 15th October, 12pm*.

Further details regarding the poster and lighting talks can be found 
here <https://www.ucl.ac.uk/research/domains/neuroscience/ucl-neuroai>.

*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.

*Sponsorship*

We are immensely grateful for the support from the Sainsbury Wellcome 
Centre <https://www.sainsburywellcome.org/web/>, the Crick Partner 
Networking Fund 
<https://www.crick.ac.uk/research/research-partnerships/university-partnerships/partnership-networking-fund> 
and AIBIO-UK <https://aibio.ac.uk/>.

We look forward to seeing you there.
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