Chris Banerji is an AI+ Senior Fellow (Clinical-Academic) and Group Leader in the Comprehensive Cancer Centre, King's College London as well as Theme Lead for Clinical AI at the Alan Turing Institute and an NHS histopathologist.

Chris trained initially in Mathematics at University of Oxford, before completing a PhD in computational and cell biology at University College London. He subsequently studied Medicine as a graduate at Imperial College London. During clinical training, he held interdisciplinary postdoctoral positions at King’s College London and the Alan Turing Institute, working at the interface of mathematics, machine learning and clinical medicine.

His current research focuses on the foundations of safe and interpretable clinical AI. In particular, he develops mathematical frameworks for aligning human and machine reasoning, including concept-based models, mechanistic interpretability, geometric approaches to deep learning, foundation models, uncertainty quantification, clinical decision support and human–AI interaction.

His work emphasises translation into real-world healthcare systems, including applications in oncology, histopathology, radiology and integrated diagnostic workflows, with a focus on safe deployment within the NHS and alignment with emerging regulatory frameworks.

Earlier in his career, Chris worked on modelling biological systems across scales, including stochastic gene expression, dynamical systems for cell–cell interactions, network and information-theoretic approaches to biological signalling, and single-cell genomics. He has contributed to biomarker discovery, cancer prognostics, stem cell biology, and rare disease research.

He is keen to collaborate across disciplines in developing mathematically grounded, clinically actionable AI systems.

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