I am a PhD student at the Institute for Multiscale Thermofluids at the University of Edinburgh. I obtained my MSc degree in Materials Science and Engineering from TU Delft in the Netherlands.

During my Master’s studies, I completed internships at Tata Steel and SKF, where my research focused on steelmaking and on understanding atomic-scale mechanisms in metallic systems through atomistic simulations. For my Master’s thesis at SKF, I evaluated the performance of recently developed universal machine learning interatomic potentials for simulating grain boundary segregation behaviour in iron grain boundaries.

In my PhD, I will continue to work in the field of machine learning potentials (MLP) and develop a MLP for studying thermal problems at solid–liquid interfaces. Specifically, my research will involve training, validating the MLP and applying it in molecular dynamics simulation studies of realistic nanomaterial–coolant liquid systems. Through these simulations, I aim to gain fundamental insights into interfacial thermal transport relevant to advanced cooling technologies and next-generation thermal management applications.