Staff Profile
Dr Matthew Forshaw
Reader in Data Science
- Email: matthew.forshaw@ncl.ac.uk
- Telephone: +44 (0)191 208 4142
- Personal Website: http://www.mattforshaw.co.uk
- Address: School of Computing,
Urban Sciences Building,
Newcastle University,
1 Science Square,
Newcastle Helix,
Newcastle upon Tyne,
NE4 5TG
Matthew is Chair of Analyst Network North East (ANNE), the regional branch of The OR Society, facilitating exchange of ideas between analysts from the academic, public and private sectors in the North East of England. Matthew holds a Senior Fellowship of the Higher Education Academy (SFHEA).
In 2018, Matthew was a visiting researcher at Systems Group, ETH Zurich (Swiss Federal Institute of Technology in Zurich).
Area of expertise: data science, stream processing, energy efficiency, distributed computing
Google Scholar: Click here.
Funding Awards
2021 Nework Rail (Co-I) “Predictability of UK Rail Network Performance Using Co-simulation and FMI-based Strategies”, £300,000
2021 Department for Education and Office for Students (PI), “Higher education short course trial: Digital Healthcare (Health informatics)” £201,617
2021 EPSRC (Joint PI), “Pedagogic innovation in (non-)cognate Data/AI Education through industry-academic co-creation.” £260,493
2021 EPSRC (PI), “Data/AI Educators Programme - Pedagogic ‘train-the-trainer’ for national capacity building in skills.” £96,000
2021 EPSRC (PI), “Grow the convening initiatives of the Data Skills Taskforce” £199,600
2021 DCMS (PI), “Foundational Data Skills for non-cognate learners”. £146,464
2021 Dept. for Digital, Culture, Media and Sport (PI), “Organisational data readiness”. £80,000
2020 Office for Students (OfS), DCMS and UK Government Office for AI (PI) “Widening access to postgraduate training in data science and AI.” £1,518,090.00
2020 UEDF (CoI) “Supporting students in Software Sustainability and Open Research.” £5,141
2019 EPSRC Industrial Cooperative Awards in Science & Technology (CASE) £87,696
2018 HEFCE Catalyst Fund (PI) “Addressing the national data analytics skills shortage: co-creation of an industry-led Data Science programme.” £250,997.86
2016 HEFCE (PI) “Improving Student Engagement and Retention through `Human in the Loop' Learning Analytics.” £102,528.77
2016 ULTSEC Innovation Fund (PI) “Promoting Student Engagement and Retention through Learning Analytics.” £13,450
- Kell AJM, McGough AS, Forshaw M. The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets. Sustainable Computing: Informatics and Systems 2021, 30, 100532.
- Kell AJM, Salas P, Mercure JF, Forshaw M, McGough AS. Deep Reinforcement Learning in Electricity Generation Investment for the Minimization of Long-Term Carbon Emissions and Electricity Costs. In: Tackling Climate Change with Machine Learning workshop at NeurIPS 2020. 2020, Climate Change AI.
- Kell AJM, Forshaw M, McGough AS. Long-term electricity market agent based model validation using genetic algorithm based optimization. In: The Eleventh ACM International Conference on Future Energy Systems (e-Energy’20). 2020, Virtual, Melbourne, Australia: ACM.
- Kell AJM, McGough AS, Forshaw M. Optimizing carbon tax for decentralized electricity markets using an agent-based model. In: The Eleventh ACM International Conference on Future Energy Systems (e-Energy’20). 2020, Virtual, Melbourne, Australia: ACM.
- Alrajeh O, Forshaw M, Thomas N. Virtual Machine Live Migration in Trace-driven Energy-Aware Simulation of High-Throughput Computing Systems. Sustainable Computing: Informatics and Systems 2020, 29(B), 100468.
- Kell AJM, Forshaw M, McGough AS. ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning. In: Tenth ACM International Conference on Future Energy Systems (ACM e-Energy). 2019, Phoenix, AZ: ACM.
- Kell AJM, Forshaw M, McGough AS. Modelling Carbon Tax in the UK Electricity Market using an Agent-Based Model. In: Tenth ACM International Conference on Future Energy Systems (e-Energy '19). 2019, Phoenix, AZ, USA: ACM.
- Kell AJM, Forshaw M, McGough AS. Optimising energy and overhead for large parameter space simulations. In: The Tenth International Green and Sustainable Computing Conference (IGSC). 2019, Alexandria, VA, U.S.A: IEEE.
- Alrajeh O, Forshaw M, McGough AS, Thomas N. Simulation of Virtual Machine Live Migration in High Throughput Computing Environments. In: IEEE/ACM 22nd International Symposium on Distributed Simulation and Real Time Applications (DS-RT). 2019, Madrid: IEEE.
- Cattermole A, Forshaw M. An Automated Approach to Cloud Performance Benchmarking. Electronic Notes in Theoretical Computer Science 2018, 340, 23-39.
- Silva PMP, Forshaw M, McGough AS. Clustering Vehicles based on Trips Identified from Automatic Number Plate Recognition Camera Scans. In: 1st International Workshop on Big Traffic Data Analytics (BigTraffic 2018). 2018, San Diego, California, USA.
- McGough AS, Forshaw M. Evaluation of Energy Consumption of Replicated Tasks in a Volunteer Computing Environment. In: 4th International Workshop on Energy-aware Simulation (ENERGY-SIM’18). 2018, Berlin: ACM.
- McGough AS, Forshaw M. Introduction to special issue on Energy-Aware Simulation and Modelling (ENERGY-SIM). Sustainable Computing: Informatics and Systems 2018, 18, 135-136.
- Kell A, McGough AS, Forshaw M. Segmenting Residential Smart Meter Data for Short-Term Load Forecasting. In: Proceedings of the Ninth International Conference on Future Energy Systems (e-Energy '18). 2018, Karlsruhe, Germany: ACM.
- Kalavri V, Liagouris J, Hoffmann M, Dimitrova D, Forshaw M, Roscoe M. Three steps is all you need: fast, accurate, automatic scaling decisions for distributed streaming dataflows. In: 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI '18). 2018, Carlsbad, CA, USA: USENIX.
- McGough AS, Forshaw M, Brennan J, Al Moubayed N, Bonner S. Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments. In: 9th International Green and Sustainable Computing Conference (IGSC 2018). 2018, Pittsburg, PA, USA: IGSC.
- Thomas N, Forshaw M, ed. Analytical and Stochastic Modelling Techniques and Applications. Springer, 2017.
- Mohamed S, Forshaw M, Thomas N. Automatic Generation of Distributed Run-time Infrastructure for Internet of Things (IoT). In: International Workshop on Engineering IoT Systems: Architectures, Services, Applications and Platforms. 2017, Gothenburg, Sweden.
- van-Moorsel A, Forshaw M, Rocha F. Experience Report: How to Design Web-Based Competitions for Legal Proceedings: Lessons from a Court Case. In: 28th International Symposium on Software Reliability Engineering (ISSRE). 2017, Toulouse, France: IEEE.
- Alrajeh O, Forshaw M, Thomas N. Machine learning models for predicting timely virtual machine live migration. In: Computer Performance Engineering: 14th European Workshop (EPEW 2017). 2017, Berlin: Springer.
- Alrajeh O, Forshaw M, Thomas N. Machine Learning Models for Predicting Timely Virtual Machine Live Migration. In: 14th European Workshop on Performance Engineering (EPEW). 2017, Berlin, Germany: Springer Verlag.
- Mohamed S, Forshaw M, Thomas N, Dinn A. Performance and dependability evaluation of distributed event-based systems: a dynamic code-injection approach. In: ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering. 2017, L'Aquila, Italy: ACM.
- Allen J, Forshaw M, Thomas N. Towards an accurate and scalable energy harvesting wireless sensor network simulator model framework. In: 3rd International Workshop on Energy-aware Simulation (ENERGY-SIM’17). 2017, L'Aquila, Italy: ACM.
- McGough AS, Moubayed NA, Forshaw M. Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems. In: ICPE 2017 Companion: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering. 2017, L'Aquila, Italy: ACM.
- Forshaw M, McGough AS, Thomas N. HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems. Concurrency and Computation: Practice and Experience 2016, 28(12), 3260-3290.
- Forshaw M, Solaiman E, McGee O, Robinson P, Emerson R. Meeting Graduate Employability Needs through Open-source Collaboration with Industry. In: ACM SIGCSE '16. 2016, Memphis, TN, USA: ACM.
- McGee O, Forshaw M, Hodgson B, Caughey S. Out of the comfort zone: Embedding entrepreneurship in a cohort of computer science doctoral students. In: ITiCSE '16 Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE. 2016, Arequipa, Peru: ACM.
- McGee O, Forshaw M, Hodgson B, Caughey S. Out of the Comfort Zone: Embedding Entrepreneurship in a Cohort of Computer Science Doctoral Students. In: ACM Conference on Innovation and Technology in Computer Science. 2016, Arequipa, Peru: ACM.
- Alrajeh O, Forshaw M, Thomas N. Performance of Virtual Machine Live Migration with Various Workloads. In: 32nd UK Performance Engineering Workshop. 2016, University of Bradford.
- Forshaw M, McGough AS, Thomas N. The case for energy-aware simulation and modelling of internet of things (IoT). In: 2nd International Workshop on Energy-Aware Simulation. 2016, Waterloo, Ontario, Canada: ACM Digital Library.
- McGough S, Forshaw M, Gerrard C, Wheater S, Allen B, Robinson P. Comparison of a cost-effective virtual Cloud cluster with an existing campus cluster. Newcastle upon Tyne: School of Computing Science, University of Newcastle upon Tyne, 2015. School of Computing Science Technical Report Series 1452.
- McGough AS, Forshaw M. Energy-aware simulation of workflow execution in High Throughput Computing systems. In: 19th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT). 2015, Chengdu, China: IEEE/ACM.
- Forshaw M, McGough AS, Thomas N. Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. Electronic Notes in Theoretical Computer Science 2015, 310, 65-90.
- Forshaw M, McGough AS. Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster. In: ENERGY-SIM 2015. 2015, Athens, Greece.
- Nguyen TH, Forshaw M, Thomas N. Operating policies for energy efficient dynamic server allocation. Electronic Notes in Theoretical Computer Science 2015, 318, 159-177.
- Forshaw M, McGough AS. Reduction of wasted energy in a volunteer computing system through Reinforcement Learning. Newcastle upon Tyne: School of Computing Science, University of Newcastle upon Tyne, 2015. School of Computing Science Technical Report Series 1451.
- Bradley J, Forshaw M, Stefanek A, Thomas N. Time-inhomogeneous Population Models of a Cycle-Stealing Distributed System. Electronic Notes in Theoretical Computer Science 2015, 318, 5-17.
- Forshaw M, Thomas N, McGough AS. Trace-driven simulation for energy consumption in High Throughput Computing systems. Newcastle upon Tyne: School of Computing Science, University of Newcastle upon Tyne, 2015. School of Computing Science Technical Report Series 1450.
- McGough AS, Forshaw M, Gerrard C, Wheater S, Allen B, Robinson P. Comparison of a cost-effective virtual cloud cluster with an existing campus cluster. Future Generation Computer Systems 2014, 41, 65-78.
- Forshaw M, McGough AS, Thomas N. Energy-efficient checkpointing in high-throughput cycle-stealing distributed systems. In: Seventh International Workshop on Practical Applications of Stochastic Modelling (PASM). 2014, Newcastle upon Tyne, UK: Elsevier BV.
- Forshaw M, McGough AS, Thomas N. On energy-efficient checkpointing in high-throughput cycle-stealing distributed systems. In: SMARTGREENS 2014 - Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems. 2014, Barcelona, Spain: SciTePress.
- Forshaw M, McGough AS, Thomas N. On Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. In: 3rd International Conference on Smart Grids and Green IT Systems (SMARTGREENS) 2014. 2014, Barcelona.
- Satvat K, Forshaw M, Hao F, Toreini E. On the privacy of private browsing - A forensic approach. In: 8th International Workshop on Data Privacy Management and Autonomous Spontaneous Security (DPM 2013). 2014, Egham, UK: Springer.
- Satvat K, Forshaw M, Hao F, Toreini E. On the Privacy of Private Browsing - A Forensic Approach. Journal of Information Security and Applications 2014, 19(1), 88-100.
- Satvat K, Forshaw M, Hao F, Toreini E. On The Privacy Of Private Browsing - A Forensic Approach (short paper). In: European Symposium on Research in Computer Security (ESORICS) 2013, 8th DPM International Workshop on Data Privacy Management. 2014, Egham, UK.
- Nguyen T, Forshaw M, Thomas N. Operating policies for energy efficient dynamic server allocation. In: 30th Annual UK Performance Engineering Workshop (UKPEW 2014). 2014, Newcastle University, Newcastle upon Tyne, UK.
- McGough AS, Forshaw M. Reduction of wasted energy in a volunteer computing system through Reinforcement Learning. Sustainable Computing: Informatics and Systems 2014, 4(4), 262-275.
- Forshaw M, Thomas N, McGough AS. Trace-Driven Simulation for Energy Consumption in High Throughput Computing Systems. In: IEEE/ACM 18th International Symposium on Distributed Simulation and Real Time Applications. 2014, Toulouse, France: IEEE.
- McGough AS, Forshaw M, Gerrard C, Robinson P, Wheater S. Analysis of power-saving techniques over a large multi-use cluster with variable workload. Concurrency and Computation: Practice and Experience 2013, 25(18), 2501-2522.
- Satvat K, Forshaw M, Hao F, Toreini E. On the Privacy of Private Browsing - A Forensic Approach. Newcastle upon Tyne: School of Computing Science, University of Newcastle upon Tyne, 2013. School of Computing Science Technical Report Series 1397.
- Bradley JT, Forshaw M, Stefanek A, Thomas N. Time-inhomogeneous Population Models of a Cycle-Stealing Distributed System. In: UK Performance Engineering Workshop. 2013, Loughborough, UK.
- Forshaw M, Thomas N. A Novel Approach to Energy Efficient Content Distribution with BitTorrent. In: Computer Performance Engineering: EPEW/UKPEW. 2012, Edinburgh, UK: Springer.
- McGough AS, Forshaw M, Gerrard C, Wheater S. Reducing the number of miscreant tasks executions in a multi-use cluster. In: Second International Conference on Cloud and Green Computing (CGC). 2012, Xiangtan: IEEE.