 I'm a theoretician at heart. I work in the application of seismology usually to the earth. I look at problems of how you extract information from complex datasets. In seismology we create a lot of complex datasets usually by measuring the vibrations of the earth from earthquakes and other natural sources or artificial sources. And the game I'm usually playing is how you can use that information to tell you something about the earth itself or the nature of the source, i.e. an earthquake. The most difficult problems in my field are thought to be unsolvable. How do we really take these complex datasets and use everything in the dataset to describe the earth or to constrain the earth? We use the information to understand physical processes in the earth, i.e. the motion of the plates and the structure. My personal buzz is about really finding a beautiful new method to do something with data that you couldn't do before, ask questions you couldn't ask before. So I find tools of analysing data to be exciting and powerful things. In some respects it's the opposite to what most scientists do. They often have a problem and then look for a tool. I do that but I'm also excited by tools that then need to find applications. Because I'm interested in data science and inference that brings me into contact with statisticians, mathematicians, physicists of course, and increasingly computer scientists and engineers. My secret has always been to talk to people from a wide variety of branches who look at similar problems and they bring fresh ideas and I think that's probably one of the more distinguishing things about my career.