Reducing the Number of Miscreant Tasks Executions in a Multi-use Cluster. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Stuart Wheater (CGC, 2012)

A Novel Approach to Energy Efficient Content Distribution with BitTorrent. - Matthew Forshaw; Nigel Thomas (EPEW/UKPEW, 2012)

Analysis of power-saving techniques over a large multi-use cluster with variable workload. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Paul Robinson; Stuart Wheater (Concurr. Comput. Pract. Exp., 2013)

Trace-Driven Simulation for Energy Consumption in High Throughput Computing Systems. - Matthew Forshaw; Nigel Thomas; A. Stephen McGough (DS-RT, 2014)

Time-inhomogeneous Population Models of a Cycle-Stealing Distributed System. - Jeremy T. Bradley; Matthew Forshaw; Anton Stefanek; Nigel Thomas (UKPEW, 2014)

Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. - Matthew Forshaw; Andrew Stephen McGough; Nigel Thomas (PASM, 2014)

Operating Policies for Energy Efficient Dynamic Server Allocation. - Thai Ha Nguyen; Matthew Forshaw; Nigel Thomas (UKPEW, 2014)

Comparison of a cost-effective virtual cloud cluster with an existing campus cluster. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Stuart Wheater; Ben Allen; Paul Robinson (Future Gener. Comput. Syst., 2014)

On the privacy of private browsing - A forensic approach. - Kiavash Satvat; Matthew Forshaw; Feng Hao 001; Ehsan Toreini (J. Inf. Secur. Appl., 2014)

Reduction of wasted energy in a volunteer computing system through Reinforcement Learning. - A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2014)

Energy-Aware Simulation of Workflow Execution in High Throughput Computing Systems. - A. Stephen McGough; Matthew Forshaw (DS-RT, 2015)

Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster. - Matthew Forshaw; A. Stephen McGough (SimuTools, 2015)

Out of the Comfort Zone: Embedding Entrepreneurship in a Cohort of Computer Science Doctoral Students. - Oonagh McGee; Matthew Forshaw; Barry Hodgson; Steve J. Caughey (ITiCSE, 2016)

Meeting Graduate Employability Needs through Open-source Collaboration with Industry. - Matthew Forshaw; Ellis Solaiman; Oonagh McGee; Hugo Firth; Paul Robinson; Ryan Emerson (SIGCSE, 2016)

HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems. - Matthew Forshaw; A. Stephen McGough; Nigel Thomas (Concurr. Comput. Pract. Exp., 2016)

Machine Learning Models for Predicting Timely Virtual Machine Live Migration. - Osama Nasser Alrajeh; Matthew Forshaw; Nigel Thomas (EPEW, 2017)

Automatic Generation of Distributed Run-Time Infrastructure for Internet of Things. - Saleh Mohamed; Matthew Forshaw; Nigel Thomas (ICSA Workshops, 2017)

Experience Report: How to Design Web-Based Competitions for Legal Proceedings: Lessons from a Court Case. - Aad P. A. van Moorsel; Matthew Forshaw; Francisco Rocha (ISSRE, 2017)

Towards an Extensible and Scalable Energy Harvesting Wireless Sensor Network Simulation Framework. - James Allen; Matthew Forshaw; Nigel Thomas (ICPE Companion, 2017)

Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems. - A. Stephen McGough; Noura Al Moubayed; Matthew Forshaw (ICPE Companion, 2017)

Performance and Dependability Evaluation of Distributed Event-based Systems: A Dynamic Code-injection Approach. - Saleh Mohamed; Matthew Forshaw; Nigel Thomas; Andrew E. Dinn (ICPE, 2017)

An Automated Approach to Cloud Performance Benchmarking. - Adam Cattermole; Matthew Forshaw (UKPEW, 2017)

Preface. - Matthew Forshaw; William J. Knottenbelt; Nigel Thomas; Katinka Wolter (PASM, 2017)

Erratum to "On the Privacy of Private Browsing - A Forensic Approach" [JISA 19/1(2014), 88-100]. - Kiavash Satvat; Matthew Forshaw; Feng Hao 001; Ehsan Toreini (J. Inf. Secur. Appl., 2017)

Simulation of Virtual Machine Live Migration in High Throughput Computing Environments. - Osama Nasser Alrajeh; Matthew Forshaw; Andrew Stephen McGough; Nigel Thomas (DS-RT, 2018)

Segmenting Residential Smart Meter Data for Short-Term Load Forecasting. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (e-Energy, 2018)

Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments. - A. Stephen McGough; Matthew Forshaw; John Brennan; Noura Al Moubayed; Stephen Bonner (IGSC, 2018)

Three steps is all you need: fast, accurate, automatic scaling decisions for distributed streaming dataflows. - Vasiliki Kalavri; John Liagouris; Moritz Hoffmann 001; Desislava C. Dimitrova; Matthew Forshaw; Timothy Roscoe (OSDI, 2018)

Evaluation of Energy Consumption of Replicated Tasks in a Volunteer Computing Environment. - A. Stephen McGough; Matthew Forshaw (ICPE Companion, 2018)

Introduction to special issue on Energy-Aware Simulation and Modelling (ENERGY-SIM). - A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2018)

Modelling Carbon Tax in the UK Electricity Market using an Agent-Based Model. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2019)

ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2019)

Optimising energy and overhead for large parameter space simulations. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (IGSC, 2019)

Students' Perception on Data Sources from Outside Virtual Learning Environment for Learning Analytics. - Andharini D. Cahyani; Lindsay F. Marshall; Matthew Forshaw (ICETC, 2019)

Preface. - Matthew Forshaw; Marco Gribaudo; William J. Knottenbelt; Nigel Thomas (PASM, 2019)

Exploring market power using deep reinforcement learning for intelligent bidding strategies. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (IEEE BigData, 2020)

Long-term electricity market agent based model validation using genetic algorithm based optimization. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2020)

Optimizing carbon tax for decentralized electricity markets using an agent-based model. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (e-Energy, 2020)

Hard Disk Failure Prediction on Highly Imbalanced Data using LSTM Network. - Cahyadi; Matthew Forshaw (IEEE BigData, 2021)

Using Virtual Machine live migration in trace-driven energy-aware simulation of high-throughput computing systems. - Osama Nasser Alrajeh; Matthew Forshaw; Nigel Thomas (Sustain. Comput. Informatics Syst., 2021)

The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2021)

Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (IEEE Big Data, 2022)

A systematic literature review on machine learning for electricity market agent-based models. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (IEEE Big Data, 2022)

Measuring Streaming System Robustness Using Non-parametric Goodness-of-Fit Tests. - Stuart Jamieson; Matthew Forshaw (EPEW, 2022)

Analysis of Reinforcement Learning for Determining Task Replication in Workflows. - Andrew Stephen McGough; Matthew Forshaw (EPEW, 2022)

Performability Requirements in Making a Rescaling Decision for Streaming Applications. - Paul Omoregbee; Matthew Forshaw (EPEW, 2022)

Towards Energy-Aware Management of Shared Printers. - Antreas Kasiotis; Chinomnso Ekwedike; Matthew Forshaw (PASM, 2022)

Machine learning applications for electricity market agent-based models: A systematic literature review. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (CoRR, 2022)

Long-term Reproducibility for Neural Architecture Search. - David Towers; Matthew Forshaw; Amir Atapour-Abarghouei; Andrew Stephen McGough (CoRR, 2022)

FEGR: Feature Enhanced Graph Representation Method for Graph Classification. - Mohamad Elhadi Abushofa; Amir Atapour Abarghouei; Matthew Forshaw; Andrew Stephen McGough (ASONAM, 2023)

On Improving Streaming System Autoscaler Behaviour using Windowing and Weighting Methods. - Stuart Jamieson; Matthew Forshaw (DEBS, 2023)

A State-Size Inclusive Approach to Optimizing Stream Processing Applications. - Paul Omoregbee; Matthew Forshaw; Nigel Thomas (EPEW, 2023)

Predicting the Performance of a Computing System with Deep Networks. - Mehmet Cengiz; Matthew Forshaw; Amir Atapour-Abarghouei; Andrew Stephen McGough (ICPE, 2023)

Visualizing ordered bivariate data on node-link diagrams. - Osman Akbulut; Lucy McLaughlin; Tong Xin; Matthew Forshaw; Nicolas S. Holliman (Vis. Informatics, 2023)

Evaluating Deep Graph Network Performance by Augmenting Node Features with Structural Features. - Mohamad Elhadi Abushofa; Amir Atapour-Abarghouei; Matthew Forshaw; A. Stephen McGough (ASONAM (3), 2024)

Reasoning Over Streaming System Performance Using Response Surface Methodology. - Stuart Jamieson; Matthew Forshaw (IEEE Big Data, 2024)

Insights from the Use of Previously Unseen Neural Architecture Search Datasets. - Rob Geada; David Towers; Matthew Forshaw; Amir Atapour-Abarghouei; A. Stephen McGough (CVPR, 2024)

Robust Streaming Benchmark Design in the Presence of Backpressure. - Iain Dixon; Matthew Forshaw; Joe Matthews 003 (EPEW, 2024)

A Plan for a Joint Study into the Impacts of AI on Professional Competencies of IT Professionals and Implications for Computing Students. - Tony Clear; Åsa Cajander; Alison Clear; Roger McDermott; Andreas Bergqvist; Mats Daniels; Monica Divitini; Matthew Forshaw; Niklas Humble; Maria Kasinidou; Styliani Kleanthous; Can Kültür; et al. (ITiCSE (2), 2024)

AI Integration in the IT Professional Workplace: A Scoping Review and Interview Study with Implications for Education and Professional Competencies. - Tony Clear; Åsa Cajander; Alison Clear; Roger McDermott; Mats Daniels; Monica Divitini; Matthew Forshaw; Niklas Humble; Maria Kasinidou; Styliani Kleanthous; Can Kültür; Ghazaleh Parvini; et al. (ITiCSE-WGR, 2024)

A Holistic Power Optimization Approach for Microgrid Control Based on Deep Reinforcement Learning. - Fulong Yao; Wanqing Zhao; Matthew Forshaw; Yang Song (CoRR, 2024)

A New Self-organizing Interval Type-2 Fuzzy Neural Network for Multi-Step Time Series Prediction. - Fulong Yao; Wanqing Zhao; Matthew Forshaw; Yang Song (CoRR, 2024)

Visualization of missing data: a state-of-the-art survey. - Sarah Alsufyani; Matthew Forshaw; Sara Johansson Fernstad (CoRR, 2024)

Constraint Optimisation Approaches for Designing Group-Living Captive Breeding Programmes. - Matthew Forshaw; Rachel Gray; Bridgett vonHoldt; Alexander Ochoa; Joshua M. Miller; Kristin E. Brzeski; Adalgisa Caccone; Evelyn L. Jensen (AAAI, 2025)

Fairness in Student Allocation and Group Formation. - Matthew Forshaw; Cristina Adriana Alexadru; Caitlin Bentley; Vladimiro González-Zelaya; Joseph Kwame Adjei; Vangel V. Ajanovski; Mireilla Bikanga Ada; Julian Brooks; Joshua Burridge; Alex Chao; Rutwa Engineer; Olga Glebova; et al. (ITiCSE (2), 2025)

A self-organizing interval type-2 fuzzy neural network for multi-step time series prediction. - Fulong Yao; Wanqing Zhao; Matthew Forshaw; Yang Song (Appl. Soft Comput., 2025)

Using Time Signal at Red (TSAR) as a tool for analysing rail network performance. - Anirban Bhattacharyya; Matthew Forshaw; David Golightly; Seb Merricks; Roberto Palacin; Ken G. Pierce; Pedro Pinto da Silva (J. Rail Transp. Plan. Manag., 2025)

A unified data-driven approach under deep reinforcement learning with direct control responses for microgrid operations. - Fulong Yao; Wanqing Zhao; Matthew Forshaw; Wenju Zhou (Knowl. Based Syst., 2025)

Data Science Students Perspectives on Learning Analytics: An Application of Human-Led and LLM Content Analysis. - Raghda Zahran; Jianfei Xu; Huizhi Liang; Matthew Forshaw (CoRR, 2025)