My research background is in experimental high-energy nuclear physics, which involves smashing together nuclei at very high energies to recreate, on a much smaller scale, the conditions in the first few microseconds after the Big Bang. This research involves collecting and analysing several petabytes of data, so I am interested in advanced techniques for handling these data and working with colleagues in computing and data science on this. The synergies on the data analysis side with machine learning and so-called explainability are a recent focus. I have an interest in the connection between the distributions of the particles produced in the collisions and the mathematics describing non-equilibrium processes. I supervise PhD students working in these areas and work to infuse this research into my teaching.