Omar Aleassa is a PhD researcher in the Faculty of Engineering and Information Technology at the University of Technology Sydney. His research focuses on underground hydrogen storage, physics-informed machine learning, reservoir simulation, and coupled hydrodynamic–geomechanical modelling. His current PhD project investigates the use of physics-informed neural networks to predict hydrogen flow behaviour, pressure distribution, caprock stress, and integrity during cyclic hydrogen injection and withdrawal. His broader research interests include renewable energy systems, hydrogen storage technologies, artificial intelligence, machine learning, and sustainable energy engineering.