I am leading a machine learning team developing efficient algorithms and systems that can evolve and learn from massive amounts of data in almost any domain, and be capable of reasoning and decision making with super-human performance.

Our systems are very effective at modelling complex relationships between variables. These might be the relationships between symptoms and diseases, or the relationships between a set of sensor inputs and the state of the system being modelled, or the relationships between cellular metabolic reactions and the genes that encode them, or the relationships between users in a social network about whom we wish to draw inferences.

More specifically, my current research projects involve
developing core machine learning algorithms and theory in probabilistic graphical models, structured learning, optimisation, and deep learning;
developing algorithms and systems for applications ranging from computer vision, social networks, healthcare, smart agriculture, smart manufacturing (Industry 4.0), automated trades etc.