My research centers on machine learning in scenarios where only limited data are available, e.g. patient specific modelling, online experimental design, and user interaction. More broadly, I am interested in problems that require us, as machine learning practioners, to
- make the most the available data and computational resources, and
- robustly quantify our model accuracy and uncertainty.
The main methodologies in my work are Gaussian processes and Bayesian optimisation.