Juan Mairal

PhD Student

Juan is currently a PhD student at the Fluid Dynamic Technologies group of the University of Zaragoza in Spain under the supervision of Dr. Javier Murillo and Prof. Pilar Garcia-Navarro. He graduated with BSc in Physics from the University of Zaragoza in 2019 and started his work with the group as a research assistant. In 2021 he moved on to get a MSc in Computational Physics from the University College Dublin and later returned to the University of Zaragoza to start work on his PhD funded by the prestigious FPU contract from the Spanish Ministry of Science. He is expected to graduate in 2026. He keeps an active collaboration with the HaeMod group from King’s College London (United Kingdom).

Juan’s research focuses on modeling 1-D networks of flows, with  application to both hydrodynamics and haemodynamics. His previous work has been focused on building robust finite-volume methods based on the exact solution of the Riemann problem at junctions and external  boundaries to tackle transient scenarios. This research has direct applications in river basin modelling and flood forecasting, as well as  prediction of the haemodynamic response of postural changes. Recently, he has started to apply Physics-Informed Machine Learning techniques to solve the inverse problem of parametrisation needed to construct personalised models. During this work, he has become interested in the potential of Physics-Informed Machine Learning to  combine partially-known physical models and some limited data to overcome the uncertainty in the parameters and the scarcity in the measurements. Additionally, he contributes as a developer of RiverFlow2D and OilFlow2D