Andrew Stephen McGough

ORCID

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 45

Top Venues

Newcastle University, Newcastle upon Tyne, UK (PHD)

Education History

Newcastle University, Newcastle upon Tyne, UK

PHD

Publications

Mohamad Elhadi Abushofa, Amir Atapour Abarghouei, Matthew Forshaw, Andrew Stephen McGough
FEGR: Feature Enhanced Graph Representation Method for Graph Classification. ASONAM (2023)
Mehmet Cengiz, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough
Predicting the Performance of a Computing System with Deep Networks. CoRR (2023)
Mehmet Cengiz, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough
Predicting the Performance of a Computing System with Deep Networks. ICPE (2023)
Michael Luke Battle, Amir Atapour-Abarghouei, Andrew Stephen McGough
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. CoRR (2022)
Becky Allen, Andrew Stephen McGough, Marie Devlin
Toward a Framework for Teaching Artificial Intelligence to a Higher Education Audience. ACM Trans. Comput. Educ. 22 (2) (2022)
Rob Geada, Andrew Stephen McGough
SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics. CVPR Workshops (2022)
Andrew Stephen McGough, Matthew Forshaw
Analysis of Reinforcement Learning for determining task replication in workflows. CoRR (2022)
David Towers, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough
Long-term Reproducibility for Neural Architecture Search. CoRR (2022)
Andrew Stephen McGough, Matthew Forshaw
Analysis of Reinforcement Learning for Determining Task Replication in Workflows. EPEW (2022)
Rob Geada, Andrew Stephen McGough
SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics. CoRR (2022)
Michael Luke Battle, Amir Atapour-Abarghouei, Andrew Stephen McGough
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. Big Data (2022)
Kenan Koc, Andrew Stephen McGough, Sara Johansson Fernstad
PeaGlyph: Glyph design for investigation of balanced data structures. Inf. Vis. 21 (1) (2022)
Ryan Curry, Cameron Trotter, Andrew Stephen McGough
Application of deep learning to camera trap data for ecologists in planning / engineering - Can captivity imagery train a model which generalises to the wild? CoRR (2021)
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. IEEE BigData (2021)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. CoRR (2020)
Rob Geada, Dennis Prangle, Andrew Stephen McGough
Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners. CoRR (2020)
John Brennan, Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, Boguslaw Obara, Andrew Stephen McGough
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks. IEEE BigData (2020)
Noura Al Moubayed, Andrew Stephen McGough, Bashar Awwad Shiekh Hasan
Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling. PeerJ Comput. Sci. 6 (2020)
John Brennan, Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, Boguslaw Obara, Andrew Stephen McGough
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks. CoRR (2020)
Amir Atapour Abarghouei, Andrew Stephen McGough, David Stanley Wall
Resolving the cybersecurity Data Sharing Paradox to scale up cybersecurity via a co-production approach towards data sharing. CoRR (2020)
Bowen Li, Denis Taniguchi, Jayathilake Pahala Gedara, Valentina Gogulancea, Rebeca Gonzalez-Cabaleiro, Jinju Chen, Andrew Stephen McGough, Irina Dana Ofiteru, Thomas P. Curtis, Paolo Zuliani
NUFEB: A massively parallel simulator for individual-based modelling of microbial communities. PLoS Comput. Biol. 15 (12) (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. CoRR (2019)
Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions. IEEE BigData (2019)
Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study. Data Sci. Eng. 4 (3) (2019)
Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions. CoRR (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Volenti non fit injuria: Ransomware and its Victims. IEEE BigData (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Volenti non fit injuria: Ransomware and its Victims. CoRR (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
A King's Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. IEEE BigData (2019)
Fady Medhat, Mahnaz Mohammadi, Sardar F. Jaf, Chris G. Willcocks, Toby P. Breckon, Peter Matthews, Andrew Stephen McGough, Georgios Theodoropoulos, Boguslaw Obara
TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text. CoRR (2019)
Mahnaz Mohammadi, Sardar F. Jaf, Andrew Stephen McGough, Toby P. Breckon, Peter Matthews, Georgios Theodoropoulos, Boguslaw Obara
On the Use of Neural Text Generation for the Task of Optical Character Recognition. AICCSA (2019)
Daniel Justus, John Brennan, Stephen Bonner, Andrew Stephen McGough
Predicting the Computational Cost of Deep Learning Models. IEEE BigData (2018)
Fady Medhat, Mahnaz Mohammadi, Sardar F. Jaf, Chris G. Willcocks, Toby P. Breckon, Peter Matthews, Andrew Stephen McGough, Georgios Theodoropoulos, Boguslaw Obara
TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text. IEEE BigData (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning. CoRR (2018)
Daniel Justus, John Brennan, Stephen Bonner, Andrew Stephen McGough
Predicting the Computational Cost of Deep Learning Models. CoRR (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning. IEEE BigData (2018)
Osama Nasser Alrajeh, Matthew Forshaw, Andrew Stephen McGough, Nigel Thomas
Simulation of Virtual Machine Live Migration in High Throughput Computing Environments. DS-RT (2018)
Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study. CoRR (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Evaluating the quality of graph embeddings via topological feature reconstruction. IEEE BigData (2017)
Noura Al Moubayed, Bashar Awwad Shiekh Hasan, Andrew Stephen McGough
Enhanced detection of movement onset in EEG through deep oversampling. IJCNN (2017)
Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough
GFP-X: A parallel approach to massive graph comparison using spark. IEEE BigData (2016)
Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough
Deep topology classification: A new approach for massive graph classification. IEEE BigData (2016)
Stephen Bonner, Andrew Stephen McGough, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Laura Moss, David Corsar, Grigoris Antoniou
Data quality assessment and anomaly detection via map/reduce and linked data: A case study in the medical domain. IEEE BigData (2015)
Andrew Stephen McGough, David Wall, John Brennan, Georgios Theodoropoulos, Ed Ruck-Keene, Budi Arief, Carl Gamble, John S. Fitzgerald, Aad P. A. van Moorsel, Sujeewa Alwis
Insider Threats: Identifying Anomalous Human Behaviour in Heterogeneous Systems Using Beneficial Intelligent Software (Ben-ware). MIST@CCS (2015)
Andrew Stephen McGough, Budi Arief, Carl Gamble, David Wall, John Brennan, John S. Fitzgerald, Aad P. A. van Moorsel, Sujeewa Alwis, Georgios Theodoropoulos, Ed Ruck-Keene
Ben-ware: Identifying Anomalous Human Behaviour in Heterogeneous Systems Using Beneficial Intelligent Software. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 6 (4) (2015)
Matthew Forshaw, Andrew Stephen McGough, Nigel Thomas
Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. Electron. Notes Theor. Comput. Sci. 310 (2015)
Andrew Stephen McGough, Isi Mitrani
Optimal Hiring of Cloud Servers. EPEW (2014)
Andrew Stephen McGough, Matthew Forshaw, Clive Gerrard, Stuart Wheater, Ben Allen, Paul Robinson
Comparison of a cost-effective virtual cloud cluster with an existing campus cluster. Future Gener. Comput. Syst. 41 (2014)
Matthew Forshaw, Andrew Stephen McGough, Nigel Thomas
On Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. SMARTGREENS (2014)
Andrew Stephen McGough, Matthew Forshaw, Clive Gerrard, Paul Robinson, Stuart Wheater
Analysis of power-saving techniques over a large multi-use cluster with variable workload. Concurr. Comput. Pract. Exp. 25 (18) (2013)
Vassilis Glenis, Andrew Stephen McGough, Vedrana Kutija, Chris G. Kilsby, Simon Woodman
Flood modelling for cities using Cloud computing. J. Cloud Comput. 2 (2013)
Andrew Stephen McGough, Matthew Forshaw, Clive Gerrard, Stuart Wheater
Reducing the Number of Miscreant Tasks Executions in a Multi-use Cluster. CGC (2012)
Andrew Stephen McGough
Developing a Cost-Effective Virtual Cluster on the Cloud. GECON (2011)
Andrew Stephen McGough, Clive Gerrard, Jonathan Noble, Paul Robinson, Stuart Wheater
Analysis of Power-Saving Techniques over a Large Multi-use Cluster. DASC (2011)
Dave Colling, Andrew Stephen McGough, Tiejun Ma, Vesso Novov, Jazz Mack Smith, David Wallom, Xin Xiong
Adding Standards Based Job Submission to a Commodity Grid Broker. CIT (2010)
Andrew Stephen McGough, Clive Gerrard, Paul Haldane, Dave Sharples, Daniel Swan, Paul Robinson, Sindre Hamlander, Stuart Wheater
Intelligent Power Management Over Large Clusters. GreenCom/CPSCom (2010)
Andrew Stephen McGough, William Lee, Shikta Das
A standards based approach to enabling legacy applications on the Grid. Future Gener. Comput. Syst. 24 (7) (2008)
Dave Colling, Andrew Stephen McGough, Jazz Mack Smith, Vesso Novov, Tiejun Ma, David Wallom, Xin Xiong
Adding Standards Based Job Submission to a Commodity Grid Broker. eScience (2008)
Ali Afzal, Andrew Stephen McGough, John Darlington
Capacity planning and scheduling in Grid computing environments. Future Gener. Comput. Syst. 24 (5) (2008)
Andrew Stephen McGough, Asif Akram, Li Guo, Marko Krznaric, Luke Dickens, Dave Colling, Janusz Martyniak, Roger S. Powell, Paul Kyberd, Constantinos Kotsokalis
GRIDCC: real-time workflow system. WORKS@HPDC (2007)
Andrew Stephen McGough, Asif Akram, Li Guo, Marko Krznaric, Luke Dickens, Dave Colling, Janusz Martyniak, Roger S. Powell, Paul Kyberd, Chenxi Huang, Constantinos Kotsokalis, Panayotis Tsanakas
GRIDCC: A Real-time Grid workflow system with QoS. Sci. Program. 15 (4) (2007)
Li Guo, Andrew Stephen McGough, Asif Akram, Dave Colling, Janusz Martyniak, Marko Krznaric
Enabling QoS for Service-Oriented Workflow on GRID. CIT (2007)
Yash Patel, Andrew Stephen McGough, John Darlington
QoS Support For Workflows In A Volatile Grid. GRID (2006)
Ali Afzal, John Darlington, Andrew Stephen McGough
QoS-Constrained Stochastic Workflow Scheduling in Enterprise and Scientific Grids. GRID (2006)
Dave Colling, Luke William Dickens, Tiziana Ferrari, Y. Hassoun, Constantinos Kotsokalis, Marko Krznaric, Janusz Martyniak, Andrew Stephen McGough, Elisabetta Ronchieri
Adding Instruments and Workflow Support to Existing Grid Architectures. International Conference on Computational Science (3) (2006)
Ali Afzal, John Darlington, Andrew Stephen McGough
Stochastic Workflow Scheduling with QoS Guarantees in Grid Computing Environments. GCC (2006)
Andrew Stephen McGough, William Lee, John Darlington
Workflow Deployment in ICENI II. International Conference on Computational Science (3) (2006)
Ali Afzal, John Darlington, Andrew Stephen McGough
Capacity Planning and Stochastic Scheduling in Large-Scale Grids. e-Science (2006)
Yash Patel, Andrew Stephen McGough, John Darlington
A Profitable Broker in a Volatile Utility Grid. Int. Trans. Syst. Sci. Appl. 2 (2) (2006)
Andrew Stephen McGough, Ali Afzal, John Darlington, Nathalie Furmento, Anthony Edward Mayer, Laurie Robert Young
Making the Grid Predictable through Reservations and Performance Modelling. Comput. J. 48 (3) (2005)
Andrew Stephen McGough, Jeremy Cohen, John Darlington, Eleftheria Katsiri, William Lee, Sofia Panagiotidi, Yash Patel
An End-to-end Workflow Pipeline for Large-scale Grid Computing. J. Grid Comput. 3 (3-4) (2005)
Andrew Stephen McGough, Isi Mitrani
Efficient parallel simulation of a sliding window protocol. Perform. Evaluation 48 (1/4) (2002)
Andrew Stephen McGough, Isi Mitrani
Parallel simulation of ATM switches using relaxation. Perform. Evaluation 41 (2-3) (2000)
Andrew Stephen McGough, Isi Mitrani
Efficient distributed simulation of a communication switch with bursty sources and losses. PADS (2000)

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Publication Activity (10 Years)

Top Topics

Top Venues

Andrew Stephen McGough