Low carbon and sustainable computing

Silhouette of two smoking chimneys and a bird in flight agains a deep orange sunset sky with a low sun

The Low Carbon and Sustainable Computing Theme groups the research in the School related to the sustainability of computing. The main focus is on reduction of emissions from computing. However, research in computing science can help in many other ways with reducing of greenhouse gas emissions and mitigation of the effects of climate change.

By 2040 emissions from computing alone will more than to half the emissions level acceptable to keep global warming below 1.5°C. This growth in computing emissions is unsustainable. The emissions from production of computing devices far exceed the emissions from operating them, so even if devices are more energy efficient producing more of them will make the emissions problem worse. Therefore we must extend the useful life of our computing devices.

The vision for Low Carbon and Sustainable Computing Theme is simple but ambitious:

  • Imagine we can extend the useful life of our devices and even increase their capabilities without any increase in energy consumption, purely through advances in Computing Science: better algorithms, better software design, better programming languages and compilers etc.
  • Meanwhile, we will develop the science and technologies for the next generation of devices, designed for energy efficiency as well as long life through pervasive hardware-software co-design.
  • Every subsequent cycle will last longer, leading to computing resources that last virtually forever and use very little energy.


For more details on the context of Low Carbon and Sustainable Computing, please read the position paper.



Academic Staff

Prof. Stephen Brewster

Stephen is a Professor of Human-Computer Interaction in the School of Computing Science at the University of Glasgow. He is a member of the GIST research section and within that, he leads the Multimodal Interaction Group doing world-leading research in human-computer interaction (mig.dcs.gla.ac.uk). His research focuses on multimodal HCI, or using multiple sensory modalities and control mechanisms (particularly audio, haptics and gesture) to create a rich, natural interaction between human and computer.

Dr. Jose Cano Reyes

José Cano Reyes is a Lecturer (Assistant Professor) in the School of Computing Science at the University of Glasgow and a visiting member of ICSA in the School of Informatics at The University of Edinburgh. His research interests are in the broad areas of Computer Architecture, Computer Systems, Compilers, Interconnection Networks, Machine Learning and Security. His current research is focused on hardware/software co-designed approaches to efficiently deploy Deep Learning applications on mobile/embedded edge devices (e.g. IoT boards, phones, drones, mobile robots).

Dr. Yehia Elkhatib

Yehia is a Reader (Associate Professor) at the School of Computing Science, Univeristy of Glasgow, UK, and is a visiting professor at École de Technologie Supérieure, Montreal. His work aims to enable distributed systems to traverse infrastructural boundaries, and to make the development and deployment of distributed systems easier. He also works on border-free network architectures in intent-driven systems, systems of systems, and information centric networks.

Dr. Jonathan Grizou

Jonathan is a Lecturer / Assistant Professor of Computing Science at the University of Glasgow and a member of their Information, Data and Analysis (IDA) research section. He received my PhD from INRIA (French National Institute for Research in Digital Science and Technology) in France for my work on self-calibration interfaces. He then was a research associate within Lee Cronin’s group at the University of Glasgow, where I led a team of nine researchers developing tools for assisting chemists in their discovery process. This involved creating a multidisciplinary mindset at the intersection of Robotics, AI, and Chemistry. I then joined the Center for Research and Interdisciplinarity (CRI) in Paris as a Research Fellow.

Dr. Marwa Mahmoud

Marwa is a Lecturer in Socially Intelligent Technologies in the School of Computing Science at University of Glasgow, and a Visiting Fellow in the Department of Computer Science and Technology at University of Cambridge, UK. Her research interests focus on computer vision for social signal processing and multimodal signal processing, especially within the context of affective computing, behaviour analytics, human behaviour understanding and animal behaviour understanding. She applied her research in the areas of automotive applications, mental healthcare, and animal welfare.

Dr Syed Waqar Nabi

Waqar’s research focus is on investigating tools and compilers for accessible heterogeneous computing, which involves working closely with a variety of languages and parallel programming frameworks. He is also interested in computing education research, where he’s been investigating work-based and competency-based learning, and also looking at ways to improve quality of CS education in developing countries.

Dr. Tim Storer

Dr Tim Storer’s research interests are in the practice of software engineering.  With respect to programming languages, a key area of interest for his research group is the practice of behaviour driven development and the expression and maintenance of specifications and automated test suites in the Gherkin specification language.  His research group have investigated the practice of behaviour driven development in industry and in open source projects, as well as designing, implementing and evaluating novel tools that support software engineers engaged in this practice.

Professor Phil Trinder

Professor Trinder's research interest is in designing, implementing, and evaluating high-level distributed and parallel programming models. Functional languages are a particular focus, so parallel Haskells, Erlang and friends.

Professor Wim Vanderbauwhede

Professor Wim Vanderbauwhede's research interest is in how programming languages, compilation and use of heterogeneous systems can reduce emissions from computing. He is also working on acceleration of scientific computing with a specific focus in simulation of severe weather evens.

Associate Members

Prof. Martin Margala

Martin is Professor of Computer Science and Director of the School of Computing and Informatics, Endowed Chair of Computer Science Eminent Scholar and Fulbright Distinguished Chair. His research interests are Digital & Mixed-Signal VLSI Design & VLSI Testing, Design for Reliability, Secure Reconfigurable Architectures and Heterogeneous Computing Architectures.

Prof. Pieter Koopman

Pieter is Universitair Docent (assistant Professor) at the Model based System Depatment department of the Institute for Computing and Information Sciences, in the Faculty of Science of the Radboud University Nijmegen, the Netherlands. His research is related to functional programming, especially the functional programming language Clean , and embedded domain specific languages.

Dr. Hans-Wolfgang Loidl

Hans-Wolfgang is an Associate Professor (Reader) in the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh. His research interests cover programming languages, parallel computation, foundations of programming, and symbolic computation. His focus area is the implementation of parallel functional languages.

Research Staff

Dr. Enrico Trombetta

Enrico is working with Dr. Jessica Enright from the FATA team and Dr. Anthony O' Hare from the University of Stirling on developing mathematical-biological models and strategies to tackle the spread of salmonid parasites such as Lepeophtheirus salmonis and Caligus salmonis, both commonly referred to by the umbrella term "sea lice". The goal is to find (pseudo-)optimal strategies to treat the lice while reducing side effects on fish population and mitigating treatment resistance development.

Dr. William Pettersson

William is interested in complexity theory, the theoretical efficiency of an algorithm, as well as the practical running-time efficiency of an algorithm or approach. Currently he is using integer programming to solve large and complex matching problems under the guidance of Dr David Manlove, and funded by EPSRC grant IP-MATCH. The goal of such research is to allow the best possible allocation of resources. For instance, one outcome of the project is an allocation of kidney donors to patients, or the allocation of student doctors to hospitals.


Selected publications

Ruairidh MacGregor, Phil Trinder, and Hans-Wolfgang Loidl. Improving ghc haskell numa profiling. In Proceedings of the 9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing, FHPNC 2021, pages 1–12, New York, NY, USA, 2021. Association for Computing Machinery.

Alejandro Llorens-Carrodeguas, Stefanos G. Sagkriotis, Cristina Cervello-Pastor, and Dimitrios P. Pezaros. An energy-friendly scheduler for edge computing systems. Sensors, 21(21), 2021.

Abdessalam Elhabbash and Yehia Elkhatib. Energy-aware placement of device-to-device mediation services in iot systems. In International Conference on Service-Oriented Computing, pages 335–350. Springer, 2021.

Tetsuya Takemi, Toshiya Yoshida, Mitsuaki Horiguchi, and Wim Vanderbauwhede. Large-eddy-simulation analysis of airflows and strong wind hazards in urban areas. Urban Climate, 32:100625, 2020.

Cristian Urlea, Wim Vanderbauwhede, and Syed Waqar Nabi. Efficient fpga cost-performance space exploration using type-driven program transformations. In 2019 International Conference on ReConFigurable Computing and FPGAs (ReConFig), pages 1–2. IEEE, 2019.

Stefanos Sagkriotis, Christos Anagnostopoulos, and Dimitrios P. Pezaros. Energy usage profiling for virtualized single board computer clusters. In 2019 IEEE Symposium on Computers and Communications (ISCC), pages 1–6, 2019.

Valentin Radu, Kuba Kaszyk, Yuan Wen, Jack Turner, José Cano, Elliot J. Crowley, Bjoern Franke, Amos Storkey, and Michael O’Boyle. Performance aware convolutional neural network channel pruning for embedded gpus. In 2019 IEEE International Symposium on Workload Characterization (IISWC), pages 24–34, 2019.

Manolis Loukadakis, Jose Cano, and Michael O’Boyle. Accelerating deep neural networks on low power heterogeneous architectures. In 11th International Workshop on Programmability and Architectures for Heterogeneous Multicores (MULTIPROG-2018), January 2018. 11th International Workshop on Programmability and Architectures for Heterogeneous Multicores (MULTIPROG-2018), MULTIPROG-2018 ; Conference date: 24-01-2018.

Claudia Vitolo, Yehia Elkhatib, Dominik Reusser, Christopher J.A. Macleod, and Wouter Buytaert. Web technologies for environmental big data. Environmental Modelling and Software, 63:185–198, 2015.

W. Vanderbauwhede, L. Azzopardi, and M. Moadeli. Fpga-accelerated information retrieval: High-efficiency document filtering. In 2009 International Conference on Field Programmable Logic and Applications, pages 417–422, 2009.