Imperial College London


Faculty of EngineeringDepartment of Earth Science & Engineering

Research Associate



c.heaney Website




Royal School of MinesSouth Kensington Campus





My research interests span several areas including:
(1) reduced-order modelling;
(2) machine-learning for scientific applications;
(3) urban and environmental flows.

I am currently working on the EPSRC-funded "RELIANT project" (Risk EvaLuatIon fAst iNtelligent Tool for COVID19), which aims to identify solutions for the management of people and spaces in the current pandemic and during the easing of restrictions.

I am a co-author of one of Wiley's top cited articles (Jan 2021 - Dec 2022): An autoencoder-based reduced-order model for eigenvalue problems with application to neutron diffusion (, which proposed using an autoencoder rather than proper orthogonal decomposition (POD) to obtain a low-dimensional space for a reduced-order model. The autoencoder can capture the behaviour of a system with fewer degrees of freedom compared to POD.



Selected Publications

Journal Articles

Heaney C, Liu X, Go H, et al., 2022, Extending the capabilities of data-driven reduced-order models to make predictions for unseen scenarios: applied to flow around buildings, Frontiers in Physics, Vol:10, ISSN:2296-424X, Pages:1-16

Heaney CE, Wolffs Z, Tómasson JA, et al., 2022, An AI-based non-intrusive reduced-order model for extended domains applied to multiphase flow in pipes, Physics of Fluids, Vol:34, ISSN:1070-6631, Pages:1-22

Obeysekara A, Salinas P, Heaney CE, et al., 2021, Prediction of multiphase flows with sharp interfaces using anisotropic mesh optimisation, Advances in Engineering Software, Vol:160, ISSN:0965-9978, Pages:1-16

Heaney CE, Buchan AG, Pain CC, et al., 2021, Reduced-order modelling applied to the multigroup neutron diffusion equation using a nonlinear interpolation method for control-rod movement, Energies, ISSN:1996-1073

Quilodrán-Casas C, Silva VS, Arcucci R, et al., 2021, Digital twins based on bidirectional LSTM and GAN for modelling COVID-19

Heaney CE, Li Y, Matar OK, et al., 2020, Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling Curves, Arxiv

More Publications