Hessam Babaee

Physics-informed neural networks for high-speed flows

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

Physics-informed machine learning

A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems

DPM: A deep learning PDE augmentation method with application to large-eddy simulation

Deep Learning of PDF Turbulence Closure

A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems

Multi-fidelity modelling of mixed convection based on experimental correlations and numerical simulations