Parallelisation study of a three-dimensional environmental flow model. - Fearghal O'Donncha; Emanuele Ragnoli; Frank Suits (Comput. Geosci., 2014)

Scaling up Deep Learning for PDE-based Models. - Philipp Haehnel; Jakub Marecek; Julien Monteil; Fearghal O'Donncha (CoRR, 2018)

Statistical and machine learning ensemble modelling to forecast sea surface temperature. - Stefan Wolff; Fearghal O'Donncha; Bei Chen (CoRR, 2019)

Precision Aquaculture. - Fearghal O'Donncha; Jon Grant (IEEE Internet Things Mag., 2019)

Localised sequential state estimation for advection dominated flows with non-Gaussian uncertainty description. - Emanuele Ragnoli; Mykhaylo Zayats; Fearghal O'Donncha; Sergiy Zhuk (J. Comput. Phys., 2019)

AllScale toolchain pilot applications: PDE based solvers using a parallel development environment. - Fearghal O'Donncha; Roman Iakymchuk; Albert Akhriev; Philipp Gschwandtner; Peter Thoman; Thomas Heller; Xavier Aguilar; Kiril Dichev; Charles Gillan; Stefano Markidis; Erwin Laure; Emanuele Ragnoli; et al. (Comput. Phys. Commun., 2020)

Using deep learning to extend the range of air pollution monitoring and forecasting. - Philipp Haehnel; Jakub Marecek; Julien Monteil; Fearghal O'Donncha (J. Comput. Phys., 2020)

Deployment and Management of Time Series Forecasts in Ocean Industry. - Fearghal O'Donncha; Albert Akhriev; Bradley Eck; Meredith Burke; Ramón Filgueira; Jon Grant (IEEE BigData, 2021)

Transfer learning to improve streamflow forecasts in data sparse regions. - Roland Oruche; Lisa Egede; Tracy Baker; Fearghal O'Donncha (CoRR, 2021)

A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales. - Fearghal O'Donncha; Yihao Hu 003; Paulito Palmes; Meredith Burke; Ramón Filgueira; Jon Grant (Ecol. Informatics, 2022)

Efficient Extraction of Insights at the Edges of Distributed Systems. - Amadou Ba; Fearghal O'Donncha; Joern Ploennigs; Muneeza Azmat (IEEE Big Data, 2023)

Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management. - Muneeza Azmat; Malvern Madondo; Arun Bawa; Kelsey Dipietro; Raya Horesh; Michael Jacobs 005; Raghavan Srinivasan; Fearghal O'Donncha (IJCAI, 2023)

A SWAT-based Reinforcement Learning Framework for Crop Management. - Malvern Madondo; Muneeza Azmat; Kelsey Dipietro; Raya Horesh; Michael Jacobs 005; Arun Bawa; Raghavan Srinivasan; Fearghal O'Donncha (CoRR, 2023)

Attention-based Domain Adaptation Forecasting of Streamflow in Data Sparse Regions. - Roland Oruche; Fearghal O'Donncha (CoRR, 2023)

Causal Temporal Graph Convolutional Neural Networks (CTGCN). - Abigail Langbridge; Fearghal O'Donncha; Amadou Ba; Fabio Lorenzi; Christopher Lohse; Joern Ploennigs (CoRR, 2023)

Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data. - Abigail Langbridge; Fearghal O'Donncha; James T. Rayfield; Bradley Eck (IEEE Big Data, 2024)

Towards Automated Solution Recipe Generation for Industrial Asset Management with LLM. - Nianjun Zhou; Dhaval Patel 002; Shuxin Lin; Fearghal O'Donncha (CoRR, 2024)

Agentic AI for Digital Twin. - Alexander Timms; Abigail Langbridge; Antonis Antonopoulos; Antonis Mygiakis; Eleni Voulgari; Fearghal O'Donncha (AAAI, 2025)

Enhancing hydrological modeling of ungauged watersheds through machine learning and physical similarity-based regionalization of calibration parameters. - Arun Bawa; Katie Mendoza; Raghavan Srinivasan; Fearghal O'Donncha; Deron Smith; Kurt Wolfe; Rajbir Parmar; John M. Johnston; Joel Corona (Environ. Model. Softw., 2025)

AssetOpsBench: Benchmarking AI Agents for Task Automation in Industrial Asset Operations and Maintenance. - Dhaval Patel 002; Shuxin Lin; James T. Rayfield; Nianjun Zhou; Roman Vaculín; Natalia Martinez Gil; Fearghal O'Donncha; Jayant Kalagnanam (CoRR, 2025)