Data-based modelling using genetic programming. - Hugo George Hiden (1998)

GOLD infrastructure for virtual organizations. - Panos Periorellis; N. Cook; Hugo Hiden; A. Conlin; M. D. Hamilton; Jiyi Wu; Jeremy W. Bryans; Xiangguo Gong; F. Zhu; R. Smith; Paul Watson 001; Allen R. Wright (Concurr. Comput. Pract. Exp., 2008)

e-Science Central for CARMEN: science as a service. - Paul Watson 001; Hugo Hiden; Simon Woodman (Concurr. Comput. Pract. Exp., 2010)

Orchestration of Grid-Enabled Geospatial Web Services in Geoscientific Workflows. - Gobe Hobona; David Fairbairn; Hugo Hiden; Philip James 002 (IEEE Trans Autom. Sci. Eng., 2010)

Achieving reproducibility by combining provenance with service and workflow versioning. - Simon Woodman; Hugo Hiden; Paul Watson 001; Paolo Missier (WORKS@SC, 2011)

A framework for dynamically generating predictive models of workflow execution. - Hugo Hiden; Simon Woodman; Paul Watson 001 (WORKS@SC, 2013)

Cloud computing for fast prediction of chemical activity. - Jacek Cala; Hugo Hiden; Simon Woodman; Paul Watson 001 (Future Gener. Comput. Syst., 2013)

Monitoring of Upper Limb Rehabilitation and Recovery after Stroke: An Architecture for a Cloud-Based Therapy Platform. - Simon Woodman; Hugo Hiden; Mark Turner 007; Stephen Dowsland; Paul Watson 001 (e-Science, 2015)

Workflow provenance: an analysis of long term storage costs. - Simon Woodman; Hugo Hiden; Paul Watson 001 (WORKS@SC, 2015)

Prediction of workflow execution time using provenance traces: Practical applications in medical data processing. - Hugo Hiden; Simon Woodman; Paul Watson 001 (eScience, 2016)

Accelerometer-based gait assessment: Pragmatic deployment on an international scale. - Silvia Del Din; Aodhán Hickey; Simon Woodman; Hugo Hiden; Rosie Morris; Paul Watson 001; Kianoush Nazarpour; Michael Catt; Lynn Rochester; Alan Godfrey (SSP, 2016)

Provenance and data differencing for workflow reproducibility analysis. - Paolo Missier; Simon Woodman; Hugo Hiden; Paul Watson 001 (Concurr. Comput. Pract. Exp., 2016)

A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and Its Users. - Mike Simpson; Simon Woodman; Hugo Hiden; Sebastian Stein 003; Stephen Dowsland; Mark Turner 007; Vicki L. Hanson; Paul Watson 001 (eScience, 2017)

Applications of provenance in performance prediction and data storage optimisation. - Simon Woodman; Hugo Hiden; Paul Watson 001 (Future Gener. Comput. Syst., 2017)

Uneven and Irregular Surface Condition Prediction from Human Walking Data using both Centralized and Decentralized Machine Learning Approaches. - Jamie McQuire; Paul Watson 001; Nick Wright; Hugo Hiden; Michael Catt (BIBM, 2021)

The e-Science Central Study Data Platform. - Paul Watson 001; Hugo Hiden (e-Science, 2022)

Mobilise-D: Experiences of Processing Large Medical Data Sets Using Cloud Computing Resources. - Hugo Hiden; Paul Watson 001 (e-Science, 2023)

A Data Efficient Vision Transformer for Robust Human Activity Recognition from the Spectrograms of Wearable Sensor Data. - Jamie McQuire; Paul Watson 001; Nick Wright; Hugo Hiden; Michael Catt (SSP, 2023)

Data Efficient Transformers for Wearable Sensor Analysis in Centralized and Federated Environments. - Jamie McQuire; Paul Watson 001; Nick Wright; Hugo Hiden; Michael Catt (IEEE Big Data, 2024)