Christopher Yau is a Reader in Computational Biology at the Institute of Cancer and Genomic Sciences where he is based at the Centre for Computational Biology and leads the Statistical Machine Learning BioHealth group.
He is an expert in statistical methodologies for machine learning and data science and specialises in genomic science particularly cancer. His research ranges from mathematical and statistical algorithm development to collaborations with experimental scientists and clinicians involving modelling real world biomedical data sets. He leads a diverse group of researchers who specialise in both experimental and computational modelling and regularly gives talks and lectures around the world on data science.
His goal is to conceive of a computational intelligence framework that will provide the foundation of learning health systems that will support novel health-related research from the molecular scale through to whole populations.
His work has been funded by the Medical Research Council, Engineering and Physical Sciences Research Council, Wellcome Trust, Ovarian Cancer Action and Cancer Research UK.
Christopher is playing a leading role in the development of Statistical Machine Learning for the Genomics England 100,000 Genomes project as sub-domain lead in Machine Learning for the Quantitative Methods, Machine Learning and Functional Genomics Clinical Interpretation Partnership. He sits on the committee of the Statistical Computing Section for the Royal Statistical Society and currently serves as a Career Development Task Force member for the Academy of Medical Sciences.