I am interested in developing principled machine learning methods, models and tools for computational and data science. My methods toolbox is primarily built on regularised learning, kernels and sparsity, as well as efficient convex/non-convex optimisation methods. My favourite topics include learning with multiple and structured targets, multiple views and ensembles. Applications of interest include metabolomics, biomedicine, pharmacology and synthetic biology.