Artificial Intelligence
Computational methods based on real intelligence
- Artificial Intelligence techniques borrow from various aspects of our understanding of how human intelligence works in order to tackle computing problems which, because of complexity or scale, are very difficult to solve by conventional programming techniques. Advances in recent years have come through the availability of greater computing power, the development of new AI techniques, and the application of ideas to new problem areas. AI technologies are strongly addressed within the School.
- Machine learning is at the heart of much of our research. Instead of working out rules to tell a computer what to do in every possible situation, it is presented with a large number of examples that it learns from.
MAIN RESEARCH AREAS
- Machine learning is applied to: video and image processing, for example for person re-identification or analysis of medical images; analysis of other data including medical; cognitive neuroscience and natural language and speech processing.
- We work on improving core AI methods, for example: fair and explainable AI; clustering algorithms; scheduling algorithms.
- In conjunction with the Computing Systems Research Theme we investigate high performance computing techniques for training and inference in machine learning.
INDUSTRIAL COLLABORATIONS
RESEARCH CENTRES AND INSTITUTIONS
ECIT
Secure, Connected, Intelligence
ENVIRONMENT/SUPPORT
Critical Mass
ECIT Atlas Research Compute Solution can be used for computationally-intensive training of machine learning models.
SPINOUT COMPANIES
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Anyvision
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EventMAP
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Brainwavebank
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Analytics Engines
STAFF
| ARTIFICAL INTELLIGENCE | Role | Interest Area | |
| Ivor Spence | Theme Lead | Heterogeneous systems, satisfiability solving | i.spence@qub.ac.uk |
| Barry Devereux | Lecturer | Natural language processing | |
| Yang Hua | Lecturer | Machine learning (vision) | |
| Anna Loughrey | Lecturer | Machine learning (bioinformatics) | |
| Barry McCollum | Senior Lecturer | Scheduling | |
| Paul McMullan | Lecturer | Scheduling | |
| Ji Ming | Professor | Speech, audio and image processing | |
| Deepak Padmanabhan | Senior Lecturer | Fairness in machine learning, ethical AI, unsupervised learning | |
| Neil Robertson | Professor | Machine learning (vision) | |
| Mai Thai Son | Lecturer | Data mining, machine learning, high performance computing | |
| Jerry Shen | Reader | Information retrieval, multimedia | |
| Roger Woods | Professor | Data analytics, specialised computer hardware |