Projects per year
Organisation profile
Organisation profile
About the group
The Solent Computing and AI research group focuses on practical aspects of computing and AI to find innovative digital solutions to real-work problems through collaborative research and industry engagement. We believe that the research should not be only on paper, but must also have an impact on industry and society in a wider sense. This group provides a vibrant platform for staff – ranging from experienced to early-career researchers – and postgraduate students to promote research culture, streamline their research activities, and produce new knowledge at the forefront of the discipline, as evidenced by peer-reviewed publications and novel solutions to the practical problems in the industry.
In 2020, the group won OfS funding of £500,000 to design and launch the postgraduate conversion course in AI and Data Science, and in 2021 we won OfS funding of £50,000 for the National Data Skills Pilot project. The research work of the group members has been included in the previous REF submissions. The group has expertise in various areas of computing including AI, machine learning, data science, computer networks, cyber security, augmented/virtual reality, user experience and usability design, software design and testing, and multimedia communications.
Areas of expertise
- AI and data science
- Multimedia communication
- Computer networks, cyber security and IoT
- Human-computer interaction, user experience and usability
- Software development and testing
- Virtual and augmented reality, immersive experience.
- Green computing
- Adaptive heuristic algorithms for search and optimisation
The group's aim
The Solent Computing and AI research group aims to:
- promote and strengthen research skills for staff and postgraduate students,
- provide a platform for coordinated and aligned research activities,
- have regular research colloquium to exchange research ideas leading to REF-able publications,
- provide consultancy to industry,
- supervise PhD research projects, and
- establish internal and external research collaborations with both academia and industry for joint projects and bidding.
Postgraduate research opportunities
The group offers supervision for MPhil/PhDs within the above-mentioned computing area or cross-disciplinary areas, especially in AI, machine learning and data science. We are accepting self-funded PhD students with suitable research proposals who will be supervised by our experienced research staff. If you would like more information about postgraduate research opportunities, please contact Dr Shakeel Ahmad. More information regarding Solent University's research programme can be found here.
Profiles
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Shakeel Ahmad, Associate Professor
- Science and Engineering - Associate Professor in Computing
- Solent Computing and AI - Research Group Convenor
Person: Academic
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Bode Amangele
- Science and Engineering - Lecturer Computing (Cyber & Com Network)
- Solent Computing and AI - Research Group Member
Person: Academic
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Jarutas Andritsch
- Science and Engineering - Lecturer in Computing
- Solent Computing and AI - Research Group Member
Person: Academic
Projects
- 1 Active
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SEAGUARD: Sea Environmental Awareness and Guard Enhanced with Unmanned AI Robotics Detection
Bhuiyan, Z., Makarchuk, D., Whitcher, A., Ahmad, S., Hasan, R., Gibson, M. & Talpur, K.
European Commission, UK Research and Innovation
1/10/24 → 31/03/27
Project: Knowledge Exchange › External Project
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A comprehensive review of existing corpora and methods for creating annotated corpora for event extraction tasks
Abdullah, M. H. A., Aziz, N., Abdulkadir, S. J., Hussain, K., Alhussian, H. & Talpur, N., 19 Nov 2024, In: Journal of Data and Information Science. 9, 4, p. 196-238 43 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile18 Downloads (Pure) -
Advanced machine learning techniques for predictive modeling of property prices
Mathotaarachchi, K. V., Hasan, R. & Mahmood, S., 22 May 2024, In: Information (Switzerland). 15, 6, 38 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile47 Downloads (Pure) -
AI-driven form analysis: Personalised strength-training feedback via computer vision techniques
Westlake, S., Andritsch, J. & Sobnath, D., 8 Jan 2024, p. 17. 1 p.Research output: Published contribution to conference › Abstract › peer-review