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Area Chair at the NeurIPS 2026 AI4Science Workshop
Dr Vinod Kumar Chauhan will serve as an Area Chair for the AI4Science Workshop at NeurIPS 2026.
Visit NeurIPS 2026Causal AI · Personalised Decisions · Healthcare
From causal insight to personalised decisions.
We develop causal and reliable AI methods for personalised decision-making, with healthcare as a central application.
Our mission
Causal AI for better personalised decisions
We develop and apply causal AI methods to understand how interventions affect individuals, compare possible actions and support decisions under uncertainty.
Our work combines methodological research with real-world applications, particularly in healthcare, where reliable personalised decisions can improve treatment selection and clinical decision support.
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Commentary accepted in The British Journal of Psychiatry
Precision psychiatry: thinking beyond simple prediction models, without dismissing them
This sole-authored commentary examines the roles of causal and non-causal prediction models in precision psychiatry. It argues that the appropriate modelling approach should be guided by the clinical need, the claims being made and the assumptions that can be justified transparently.
Read the commentary3
A Practical Tutorial on Agentic AI
Our new preprint, “A Practical Tutorial on Agentic AI”, provides a practical introduction to agentic AI.
Read the preprint4
Funded PhD studentship in Agentic AI for Dementia Care (Home students only)
CAIH Lab is recruiting a Home student for a funded PhD studentship in Agentic AI for Dementia Care.
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Associate Editor, BioData Mining
Dr Vinod Kumar Chauhan is joining BioData Mining as an Associate Editor.
Visit BioData MiningSelected work
Featured publications
Position: Causal AI for Personalised Treatments Needs Holistic Approach
Beyond Correlations: The Necessity and the Challenges of Causal AI
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes
A Practical Tutorial on Agentic AI
Precision psychiatry: thinking beyond simple prediction models, without dismissing them
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We welcome motivated students, researchers and collaborators interested in advancing causal AI, agentic AI and personalised decision-making, including their application to healthcare.
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