Dr George Wilson

George has taught many aspects of computer science (programming languages, distributed applications, spatial data processing, artificial intelligence) and has research experience in all these areas.

[email protected]

Background

Originally with a Geosciences background, George moved into Computer Science developing a teaching focus on high-level programming languages (C#, C/C++, Java, MatLab), Artificial Intelligence, Computer Graphics, Image Processing and Distributed Programming. His responsibilities include Chair of the School Research Ethics Panel, Link Tutor for an overseas partner institute (SAM, Trinidad), and management of the undergraduate Final Year projects. His research interests and activities are broad. He regularly reviews academic papers and has served as organising committee member with track chair responsibility for two international IEEE conferences (ISIE2017, INDIN2015). George has been Part-Time since October 2021.

Research interests

Spatial Data Processing (geographic data, images); Artificial Intelligence (healthcare data analytics, financial market forecasting) and Computer Systems (network power management, computer architecture). George is a member of our Computing, Informatics and Applications research group.

Areas of research supervision

George has supervised a number of research students to successful PhD completion in the following areas: distributed applications and web services; web semantics; software reliability.

Teaching

• Mainly BEng (Hons) Computer Science

Qualifications

• PhD Isotope Geochemistry, University of Bath, UK
• MSc Geochemistry, University of Leeds, UK
• MSc Computer Science, Anglia Ruskin University, UK
• BSc (Hons) Geology, Aberystwyth University, UK

Memberships, editorial boards

• Professional Member, the British Computer Society (MBCS)
• Senior Fellow, the Higher Education Academy (SFHEA)

Research grants, consultancy, knowledge exchange

• Lead Academic for Knowledge Transfer Partnership with AT Technology Services Ltd on use of Data Analytics to improve Healthcare Provision. Project awarded 'Outstanding' grade by Innovate UK in 2022.
• Secured and managed three other UK/EU-funded Knowledge Exchange projects with industrial partners (KEEP/KTP), developing their Business Information Systems.
• Occasional consultancy/educational training courses delivered externally.

Selected recent publications

Shirazibeheshti, A.; Ettefaghian, A.; Khanizadeh, F.; Wilson, G.; Radwan, T. and Luca, C. (2023). Automated Detection of Patients at High Risk of Polypharmacy including Anticholinergic and Sedative Medications. International Journal of Environmental Research and Public Health; Special Issue Editorial Board Members' Collection Series: Artificial Intelligence and Mathematical Modeling for Public Health — An Agenda for the Future, 20(12); 6178: https://doi.org/10.3390/ijerph20126178.

Fitzjohn, j.; Winckles, A.; Wilson, G. and Vicinanza, D. (2022). A Software Development Kit and translation layer for executing Intel 8080 assembler on a Quantum Computer. IEEE Transactions on Quantum Engineering (Journal), v3, p1-12. IEEE Xplore DOI: 10.1109/TQE.2022.3204653.

Recent presentations and conferences

Dinita, R.; Cirstea, M. and Wilson, G. (2023). Novel Autonomous Software for Enhanced Datacenter Operational Efficiency and Botnet Detection. IECON23 49th Annual Conference of the IEEE Industrial Electronics Society (IES). 16-19th October 2023, Singapore; paper 000627. 9pp. DOI: 10.1109/IECON51785.2023.10311667.

Chakraborty, A.; Wilson, G. B; Luca, C. and Biba, M. (2022). An Optimised Morphological Image Processing Method suitable for the Early Detection of Diabetic Retinopathy. 18th International Conference on Intelligent Computer Communication and Processing (IEEE ICCP), 22-24th September 2022, Cluj-Napoca, Romania. 6pp. DOI: 10.1109/ICCP56966.2022.10053986.

Shirazibeheshti, A.; Radwan, T.; Ettefaghian, A.; Khanizadeh, F.; Wilson, G. and Luca, C. (2022)  Clustering for detection of the population at risk of anticholinergic medication. International Conference on Digital Healthcare (ICDH 2022: XVI), 28-29th January 2022, New York, US, (Proceedings p253-257; paper p57-61.  https://publications.waset.org/10012501/pdf).

Milke, V., Luca, C., Wilson, G. and Fatima, A. (2020). Using Convolutional Neural Networks and raw data to model Intraday Trading market behaviour. Proceedings of the IEEE 2020 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), 22-24 February 2020, Valletta, Malta. DOI:10.5220/0008992402240231, p224-231.