Dr Marc Roper

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Computer and Information Sciences

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Personal statement

My research is primarily focused on the area of software engineering, and in particular the development and evaluation of techniques to support the construction and evolution of more reliable and robust software systems. A common theme in much of this work is the application of machine learning to software engineering problems; for example, to automatically generate program test data, predict software project costs, perform intrusion detection, identify the root location of faults within systems, and automatically detect software system failures. The latter of these in particular makes extensive use of a range of both semi-supervised and unsupervised (clustering) machine learning algorithms to detect anomalous entries in large very high-dimensional and complex data sets. More recently I have also been turning my attention to the converse problem of testing AI systems.

My expertise and interests in machine learning extend outside the software engineering domain and I have employed clustering and classification algorithms in a variety of other contexts such as the automatic identification of potential road accident blackspots from crowdsourced smartphone sensor data, and the detection of objects within images.

I also have extensive experience of using machine learning in a variety of industrial projects such as forecasting customer buyer behaviour, predicting building energy performance, and modelling interventions to combat sedentary behaviour.

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Area of Expertise

  • Software Engineering (particularly design, testing and debugging)
  • Data Analytics
  • Machine Learning
  • Conducting empirical studies of software engineering techniques and processes
  • Search-based software engineering
  • Software analytics (static analysis, dynamic analysis and repository mining)
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Publications

Development and validation of a digital biomarker predicting acute kidney injury following cardiac surgery on an hourly basis
Lapp Linda, Roper Marc, Kavanagh Kimberley, Schraag Stefan
JTCVS Open, pp. 1-42 (2023)
https://doi.org/10.1016/j.xjon.2023.09.023
Dynamic prediction of patient outcomes in the intensive care unit : a scoping review of the state-of-the-art
Lapp Linda, Roper Marc, Kavanagh Kimberley, Bouamrane Matt-Mouley, Schraag Stefan
Journal of Intensive Care Medicine Vol 38, pp. 575-591 (2023)
https://doi.org/10.1177/08850666231166349
Beyond the clinic : maximum free-living stepping as a potential measure of physical performance
Speirs Craig, Dunlop Mark D, Roper Marc, Granat Malcolm
Sensors Vol 23 (2023)
https://doi.org/10.3390/s23146555
Definition and classification of postoperative complications after cardiac surgery : a pilot Delphi study
Lapp Linda, Bouamrane Matt-Mouley, Roper Marc, Kavanagh Kimberley, Schraag Stefan
JMIR Perioperative Medicine Vol 5 (2022)
https://doi.org/10.2196/39907
Predicting the onset of delirium on hourly basis in an intensive care unit following cardiac surgery
Lapp Linda, Roper Marc, Kavanagh Kimberley, Schraag Stefan
2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS) , pp. 234-239 (2022)
https://doi.org/10.1109/cbms55023.2022.00048
Towards evolution-based autonomy in large-scale systems
Anderson Damien, Harvey Paul, Kaneta Yusaku, Papadopoulos Petros, Rodgers Philip, Roper Marc
GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference GECCO 2022 GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference, pp. 1924–1925 (2022)
https://doi.org/10.1145/3520304.3533975

More publications

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Teaching

Over my career I have taught a lare range of classes, from 1st year undergraduate to postgraduate, mainly on areas related to programming, software engineering, software design, data analytics and machine learning.

My main current teaching responsibilities are:

I am also responsible for overseeing the MEng final year group project:

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Research Interests

  • Software engineering
  • Machine Learning

Professional Activities

Chief External Examiner, Heriot-Watt University, School of Mathematical and Computer Science
Examiner
2023
Clinical Trials Data Workshop
Organiser
17/11/2022
IEEE International Conference on Artificial Intelligence Testing (AITest)
Chair
23/8/2021
IEEE International Conference On Artificial Intelligence Testing (AITest)
Chair
3/8/2020
IEEE International Conference on Artificial Intelligence Testing (AITest)
Chair
4/4/2019
External Examiner for PGT programme, Department of Informatics, King’s College London,
Examiner
2019

More professional activities

Projects

KTP - Coolside Ltd t/a Trtl. Development of a platform to proactively determine and address ongoing counterfeiting and unauthorised product distribution
Roper, Marc (Principal Investigator) Dickson, Alexander (Co-investigator) Wallace, William (Co-investigator)
01-Jan-2022 - 28-Jan-2025
AI and blockchain for construction, mining and infrastructure companies - Hypervine / Data Lab
Roper, Marc (Principal Investigator) Roberts, Jen (Co-investigator)
01-Jan-2022 - 31-Jan-2022
Providing confidence to encourage active travel through the application of AI
Dunlop, Mark (Principal Investigator) Roper, Marc (Co-investigator)
01-Jan-2020 - 28-Jan-2021
Maths DTP 2020 University of Strathclyde | Murray, Andrew
Roper, Marc (Principal Investigator) Arulselvan, Ashwin (Co-investigator) Murray, Andrew (Research Co-investigator)
01-Jan-2020 - 01-Jan-2025
KTP - Maru Syngro
Barlow, Euan (Principal Investigator) Revie, Matthew (Co-investigator) Roper, Marc (Co-investigator)
15-Jan-2018 - 14-Jan-2020
Optimising Industrial Service Workforces using Mobile App Data
Roper, Marc (Principal Investigator) Minisci, Edmondo (Co-investigator) Riccardi, Annalisa (Co-investigator)
01-Jan-2018 - 01-Jan-2019

More projects

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Contact

Dr Marc Roper
Reader
Computer and Information Sciences

Email: marc.roper@strath.ac.uk
Tel: 548 2956