Chris is a CRUK funded Senior Research Fellow at the Comprehensive Cancer Centre and Theme Lead for Clinical AI at the Alan Turing Institute, as well as an NHS histopathologist at University College London Hospitals. Prior to joining King's, Chris studied Mathematics at Oxford before undertaking his PhD in computational and cell biology at UCL. After his PhD he studied medicine as a graduate at Imperial College London.

During his clinical training he held a part-time postdoctoral positions at King’s College London and the Alan Turing Institute facilitating his ongoing research. As an interdisciplinary clinician-scientist Chris has a strong interest in mathematical and computational approaches to big biomedical data analysis, with the aim of developing robust and translatable clinical AI.

His previous work has focused on understanding pathological heterogeneity at all levels (from molecular to clinical) and includes biomarker and therapeutic discovery in muscular dystrophy, cancer prognostics and stem cell biology. His academic work has been recognised by several international prizes, including the Muscular Dystrophy UK President’s Award for best Early Career Researcher. Chris is particularly interested developing safe, translatable clinical AI, to improve NHS services. His current work is aligned to multimodal data integration, personalised uncertainty quantification, transparent AI and the geometry of deep learning.

Chris has also published on stochastic modelling of gene expression, dynamical systems applied to cell-cell interactions, single cell/nuclear RNA-seq, network theory (applied to protein interactions), information theory (applied to biological signal transduction), transcriptomic biomarkers, cellular differentiation (in particular muscle regeneration and malignancy), clinical subtyping in heterogeneous pathology and classification approaches, dynamic image analysis, and importantly rare diseases. He would be delighted to discuss any of these topics and welcomes collaboration.

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