Neuro AI: Where Artificial Intelligence Meets the Human Brain

Matthew Brown

Research-strategy leader, Wellcome

Dr Matthew Brown is a research-strategy leader working at the intersection of digital technology and global mental health. He is currently Head of Digital Technology, Mental Health & Life Sciences at Wellcome, where he leads strategic portfolios that accelerate the development, evaluation and responsible adoption of data-driven tools for mental health and the broader life sciences

Trained as a neuroscientist, Matthew holds a DPhil from the University of Oxford and has conducted research across cellular, circuit and cognitive neuroscience, with previous academic posts at Imperial College London and the University of Geneva. He brings this deep scientific grounding to his current work shaping large-scale research investments and collaborative programmes.

At Wellcome, Matthew manages portfolios spanning digital mental-health technologies, foundational neuroscience infrastructure, data access, software, and skills development. His work includes co-designing new models for international neuroscientific collaboration, supporting regulatory guidance for digital mental-health tools, and establishing capacity-building initiatives such as the first African Bioinformatics Institute.

Matthew has extensive experience working across academia, philanthropy, industry and regulation, and currently serves on several advisory and steering boards, including for the Alzheimer’s Disease Data Initiative and the MHRA. He is passionate about strengthening the neuroscience ecosystem through collaboration, open science and inclusive research cultures.

Mark Elliott:

Director, Professor of Data Science , SPRITE+

Mark Elliot has worked at the University of Manchester since 1996, mainly in the field of statistical confidentiality, founding the international renowned Confidentiality and Privacy Research Group (CAPRI) in 2002, and has managed numerous research projects within CAPRI remit.

​He is one of the key international researchers in the field of Statistical Disclosure and collaborates widely with non-academic partners, particularly with national statistical agencies where he has been a key influence on disclosure control methodology used in censuses and surveys and where the SUDA software that he developed in collaboration with colleagues in Computer Science at Manchester is used. 

Since 2012, he has led the UK Anonymisation Network, which has 600 members and provides advice, consultancy and training on anonymisation. 

Aside from Confidentiality, Privacy and Disclosure, his research interests include Data Science Methodology and its application to social science. He is director of the University’s new interdisciplinary MSc in Data Science and the doctoral programme in Data analytics and society.

Valentina Escott-Price

Group Leader, Dementia Research Institute (UK DRI) at Cardiff University

Prof. Valentina Escott-Price is a leading big-data researcher who applies advanced ML and AI to large genomic, clinical, and multimodal datasets to identify risk genes and biological pathways involved in disease. After studying mathematics at St. Petersburg University, she earned her PhD in Statistics from Cardiff University in 2001. She has worked in Cardiff’s Department of Psychological Medicine since 2002 and joined the UK Dementia Research Institute in 2017, where she leads the Bioinformatics and Functional Genomics programme. Combining strengths in mathematics, programming, biostatistics and genetics, she develops innovative computational approaches to illuminate mechanisms of complex disorders.

Karl Friston

Professor of Imaging Neuroscience/Wellcome Principal Research Fellow, University College London

Karl Friston is a world-renowned British neuroscientist and theoretician, widely regarded as one of the most influential scientists of the modern era. Currently a Professor at University College London, his work has fundamentally reshaped our understanding of the human brain.

Friston first gained international acclaim in the 1990s by inventing Statistical Parametric Mapping (SPM). This mathematical framework became the global standard for analysing neuroimaging data, allowing scientists to pinpoint exactly which areas of the brain "light up" during specific tasks. He followed this with Voxel-Based Morphometry, further revolutionising how we measure brain structure.

In recent years, Friston has shifted toward "grand unified theories" of biology. He developed the Free Energy Principle, a provocative mathematical theory suggesting that all living systems—from single cells to entire societies—act to minimise "surprise" or uncertainty about their environment. This concept of the brain as a "prediction machine" has profound implications for artificial intelligence, philosophy, and our understanding of mental health conditions like schizophrenia.

A Fellow of the Royal Society and one of the most highly cited researchers in history, Friston’s multidisciplinary approach continues to bridge the gap between physics, biology, and computer science.

Heidi Johansen-Berg

Pro-Vice Chancellor (Strategic Initiatives) and Associate Head (Research and Innovation) , University of Oxford

Heidi Johansen-Berg FRS FMedSci is Pro-Vice Chancellor (Strategic Initiatives) at the University of Oxford and Associate Head (Research and Innovation) in the Medical Sciences Division. Heidi also is a Wellcome Principal Research Fellow and member of the Oxford University Centre for Integrative Neuroimaging (OxCIN). Heidi's research group investigates plasticity and recovery in the sensorimotor system, with particular focus on white matter plasticity and activity-dependent myelination. Her research focuses on how the brain changes with learning, experience, and damage.  As well as shedding light on how the healthy brain responds to change, her work also has implications for understanding and treating disease. 

Sieun Lee

Research Fellow, Neurotechnology and TIPSS, SPRITE+

Sieun Lee is a Research Fellow with SPRITE+, exploring the future evolution of neurotechnology and its implications for trust, identity, privacy, safety, and security. She brings an interdisciplinary background in biomedical engineering and data-driven health research, developing computational methods for large-scale neuroimaging and health data to translate complex evidence into insights on neurodegeneration and mental health. Previously, she was a Research Fellow at the University of Nottingham supported by the MRC Digital Youth programme and NIHR Nottingham Biomedical Research Centre (2022-2025), and a University of Nottingham Precision Imaging Beacon Fellow (2021-2022).

Narender Ramnani

BNA President/ Professor of Neuroscience, Royal Holloway, University of London

Professor Ramnani is a distinguished Professor of Neuroscience at Royal Holloway, University of London, where his research group uses functional neuroimaging to understand brain organisation, and brain mechanisms that govern higher cognitive function, learning processes, and the control of action.

He is also Vice Dean for EDI at Royal Holloway’s School of Life Sciences and the Environment. Beyond his university roles, he is a member of the Parliamentary and Scientific Committee APPG Advisory Group. He also makes contributions to equity, diversity, and inclusion through his contributions to the BNA Scholars programme, his role on the BBSRC's Expert EDI Advisory Group and his governance role as a member of the Governance Committee of Advance HE's Race Equality Charter. A commitment to fostering a strong, collaborative, and inclusive research community underscores the priorities he brings to the Presidency.

Maneesh Sahani

Director, Gatsby Computational Neuroscience Unit

Professor Maneesh Sahani is a British-based computational neuroscientist and machine-learning researcher known for his work on how the brain performs complex computations such as perception, learning, and decision-making. He is a Professor of Theoretical Neuroscience and Machine Learning at University College London (UCL) and serves as Director of the Gatsby Computational Neuroscience Unit, one of the world’s leading research centres linking neuroscience and artificial intelligence.

Christopher Summerfield

Professor of Cognitive Neuroscience, University of Oxford

Christopher Summerfield is Fellow by special election and principal investigator at the Summerfield lab which conducts research into how humans make decisions.

Chris Summerfield was trained in psychology and neuroscience at University College London, Columbia University (New York), and the École normale supérieure (Paris).  He is Professor of Cognitive Neuroscience in the department of Experimental Psychology, where he heads a lab focussed on understanding the computational mechanisms by which humans make decisions, and how these processes are implemented in the brain.  His work, which involves a combination of computer simulations, behavioural testing, and functional brain imaging, is funded by a grants from the European Research Council, the Wellcome Trust, and the National Institute of Health.