UCL NeuroAI

About 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.
Upcoming NeuroAI events
Previous talks
- June 2022 | Dr Grace Lindsay
Talk title: "Attention in Psychology, Neuroscience, and Machine Learning"
Speaker: Dr Grace Lindsay, New York University
Date: Wednesday 15 June 2022- April 2022 | Professor Nathaniel Daw
Talk title: "Tractable, compositional linear approximations to planning in the brain"
Speaker: Nathaniel Daw, Princeton University
Date: Wednesday 20 April 2022- February 2022 | Dr Kelsey Allen
Talk title: "Towards a recipe for physical reasoning in humans and machines"
Speaker: Dr Kelsey Allen, DeepMind
Date: Wednesday 16 February 2022- November 2021 | Dr Will de Cothi
Talk title: "Learning predictive maps in the brain for spatial navigation"
Speaker: Dr Will de Cothi, University College London
Date: Wednesday 17 November 2021- October 2021 | Dr Rebecca Jackson
Talk title: "Reverse-Engineering the Cortical Architecture for Controlled Semantic Cognition"
Speaker: Dr Rebecca Jackson, University of Cambridge
Date: Wednesday 13 October 2021- September 2021 | Professor Michael Milford
Talk title: "Spatial and Perceptual Neuroscience Questions a Roboticist Would Love to Have Answered"
Speaker: Professor Michael Milford, Queensland University of Technology
Date: Wednesday 15 September 2021- July 2021 | Alexander Terenin
Talk title: "Physically Structured Neural Networks for Smooth and Contact Dynamics"
Speaker: Alexander Terenin, Imperial College London
Date: Wednesday 9 June 2021- June 2021 | Dr Ida Momennejad
Talk title: "Toward Human-like RL"
Speaker: Dr Ida Momennejad, Microsoft Research NYC
Date: Wednesday 9 June 2021- March 2021 | Kimberly Stachenfeld
Talk title: "Graph Representation Learning and the Hippocampal-Entorhinal Circuit"
Speaker: Kimberly Stachenfeld, DeepMind
Date: Wednesday 17 March 2021- February 2021 | Daniel Yamins
Talk title: "Self-Supervised Learning for Neuroscience and Artificial Intelligence"
Speaker: Daniel Yamins, Stanford University
Date: Wednesday 17 February 2021- January 2021 | Benigno Uria
Talk title: "The Spatial Memory Pipeline: a deep learning model of egocentric to allocentric understanding in mammalian brains"
Speaker: Benigno Uria, DeepMind
Date: Wednesday 13 January 2021- November 2020 | Professor Netta Cohen
Talk title: "The brain map of a worm: A multiscale connectome derived from whole-brain volumetric reconstructions"
Speaker: Professor Netta Cohen, University of Leeds
Date: Wednesday 11 November 2020- October 2020 | Dr Aldo Faisal
Talk title: "Brains as human-in-the-loop AI systems"
Speaker: Dr Aldo Faisal, Imperial College London
Date: Wednesday 14 October 2020- September 2020 | Professor Michael Bronstein
Talk title: "Geometric deep learning on graphs and manifolds"
Speaker: Professor Michael Bronstein, Imperial College London
Date: Wednesday 16 September 2020- July 2020 | Dr Irina Higgins
Talk title: "Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons"
Speaker: Dr Irina Higgins, Google Deepmind
Date: Wednesday 15 July 2020
Previous annual event
- July 2022
Date: Monday 11 July 2022
UCL's Annual NeuroAI event featured speakers working across the spectrum of machine learning and neuroscience. This event fostered further collaboration and discussion.
Speakers: Professor Peter Latham (Gatsby Computational Neuroscience Unit, UCL), Dr Raia Hadsell (DeepMind), Professor Blake Richards (McGill University), Dr Kim Stachenfeld (DeepMind)
Event programme:
1.00pm – Welcome
1.05pm – 2.35pm – Session one
Kim Stachenfeld (DeepMind) "Predictions and Relations for Biological and Artificial Reasoning"
Peter Latham (UCL) "Why Dale’s law?"
Blake Richards (McGill University) "Contrastive introspection to rapidly identify contingencies in the environment"
2.35pm - 2.55pm – Comfort break
2.55pm – 3.55pm – Session two
Raia Hadsell (DeepMind) "Embodied AGI and The Future of Robotics"
Panel discussion
3.55pm - 4.00pm – Closing remarks
4.00pm - 5.00pm – Drinks reception
- May 2021
Date: Wednesday 12 May 2021
UCL's Annual NeuroAI event featured speakers working across the spectrum of machine learning and neuroscience. This event fostered further collaboration and discussion.
Speakers: Professor Alexander Mathis (Swiss Federal Institute of Technology, EPFL), Professor Claudia Clopath (Bioengineering Department, Imperial College London), Professor Daniel Alexander (UCL Department of Computer Science), Dr Jennifer Collinger (Department of Physical Medicine and Rehabilitation, University of Pittsburgh)
Full programme available here.