Kate Kemsley read Physics at Magdalen College, Oxford. After graduating, she worked for some years as a Patent Examiner at the European Patent Offices in The Hague and Berlin, before returning to the UK and to academia.

Her PhD and early career at the UK's Institute of Food Research focused the design of novel sensors, and quantitative applications of infrared and Raman spectroscopy. Subsequently, she concentrated on multivariate statistics – a family of computational methods particularly useful for handling the large datasets produced by modern analytical techniques. Applications of these methods have included natural product integrity issues, including detecting adulteration of edible oils, processed fruits, meat products, coffee and spices.

The arrival of ‘omics and other high-throughput analytical technologies opened up new opportunities for the data scientist. Kate’s interests expanded to include the application of computational statistics and machine learning to wide range of data types, from studies involving the metabolomics platform technologies (NMR, GC-, LC-MS) through electrophoresis, hyperspectral and chemical imaging. She also has a long-standing interest in the processing of electromyograms and other time-domain digital waveforms.

Recently she has acted as a consultant for QIBExtra at Quadram Institute Bioscience, a subsidiary company of UEA. Her current work has a focus on NMR spectroscopy, developing a variety of methods for biochemical analysis. Much of her research is aligned to industrial application, on which she collaborates closely with a range of commercial partners.