All postgraduate researchers are registered in the University’s Graduate School and housed in the faculty or department that is most appropriate for the project on which they are working. PGRs working on computer science and informatics projects are normally housed in the Department of Computer Science.
Research in the Department of Computer Science is organised around several broad themes promoted and supported by the Department’s Centre for Data and Complex Systems as well as its Visual Computing Lab. While the majority of the work falls under the data analytics and visualisation themes, other contributions focus on disruptive technologies and infrastructure. Research in the areas of robotics, visual computing, virtual and augmented reality, all are supported by our state-of-the-art, high-end research facilities. Our close links with local, national and international organisations allow us to work on real word challenges. We are committed to interdisciplinary work which is achieved by being part of an interdisciplinary research centre for Data Science and also working with three research institutes in the University. We have been successful in attracting funding from major national and international funding bodies. We have a well-established, growing postgraduate and postdoctoral research community supported by in house and external training and personal development opportunities.
The University particularly welcomes applications for studentships in the project areas outlined below with additional research information on the research area webpages. All PGRs will be supported by a supervisory team with appropriate expertise. Also, see the University’s research repository for further information on the research outputs of each member of staff.
In the first instance please direct all enquiries about proposed projects on topics related to Computer Science and Informatics to the Graduate School with Professor Ella Pereira, Graduate School Research Degree contact for Computer Science and Informatics.
- Big data analytics, machine and deep learning, real-time machine learning, resource-efficient machine learning, decentralised/distributed data analytics, classification imbalance, feature design and analysis, industry 4.0 analytics.
- Data mining, pattern recognition & semantic analysis, Natural Language Processing and text mining, social media mining.
Visual computing and visualisation
- Augmented and virtual reality, computer vision, visual computing, wearable computing.
- 3D computer graphics, data visualisation, visual data analytics, machine vision.
- 3D vision, object recognition, advanced analytics, image/video analytics, pattern recognition.
Disruptive technologies and infrastructure
- Autonomous systems, robotics and systems automation, cloud computing, wireless communications, telecommunications
- IoT enabled smart systems, applied machine/deep learning, intelligent transport, digital healthcare, agriculture and industry 4.0
- Digitalisation via 5G, satellite and 5G convergence
- Robotics Systems, including: legged robots, manipulators, wheeled robots, and soft robots
- 3D Modelling – open-source 3D printing to support robot structure development.
- Security and privacy problems in healthcare management
- Blockchain based security and privacy enhancing technologies and applications
- Security and privacy by design (including automated verification methods of security systems)
- Security and privacy problems of internet of things applications
- Security and privacy problems of biometrics systems and applications
Interdisciplinary STEM projects
- Medical informatics, bio-inspiring computing, plant diseases, and so on.