Bioinformatics and biomedical data analytics
We develop data mining and data analytics methods for biomedical applications and bioinformatics, particularly to support decision making in the biomedical domain. We investigate how to better diagnose and treat paediatric cancer with the aim of helping clinicians to identify which children are unlikely to respond to treatment and to create a tool for 'personalised medicine' where therapies are individually tailored. Our visualisations of patients based on their gene activity, genetic variations, clinical data and treatment outcomes can be used to objectively compare new patients with previous patients. Our computer-aided diagnosis methods assist pathologists by identifying and counting histological structures in scanned images of tumour samples. We work with parasitologists to develop a bioinformatics vaccine discovery pipeline for several eukaryote parasites.
Cloud computing
We focus on developing breakthrough research solutions that can be used practicably by the industry, to pave the development and deployment of the next generation e-services in the Cloud. We develop innovative and practical solutions to ensure the reliability of cloud services, for ensuring the security and privacy of data stored in cloud services, for developing personalised cloud services (taking into account the consumer’s requirements), intelligent methods for cloud service selection; intelligent methods for self-healing cloud service delivery by independent cloud service monitoring; and intelligent methods for indexing, retrieving and composing cloud services. Additionally, we investigate the use of cloud technologies such as MapReduce and Hadoop for advantaged Cloud-based Analytics. In order to ensure that the solutions are practical we collaborate with industry across a number of verticals such as transportation, health, education and finance. We actively seek qualified potential students to work in this group.
Computational intelligence
We focus on computational methodologies and approaches of artificial neural networks, evolutionary computation and fuzzy logic, as well as swarm intelligence, to address complex real-world problems. In particular, we develop models, algorithms, and software tools for fuzzy optimization, fuzzy prediction, fuzzy neural networks, fuzzy support vector machine, fuzzy data analytics as well as various applications of soft computing.
Conceptual modelling
Conceptual modelling for software engineering – both processes and products – relies on a solid underpinning, typically provided by a metamodel or an ontology. Relationships between models, metamodels and ontologies are explored in the context of seeking a unifying theory based on language use, philosophy and mathematics. Application of these ideas is oriented towards situational method engineering in the fields of object technology (eg. OPF, the OPEN Process Framework) and agent-oriented methodologies. This work also contributes significantly to international standards, including ISO/IEC 24744, UML and SPEM. Within COTAR [link here] we also encompass research in OO metrics and quality management.
Creativity and cognition in digital media
Creativity and Cognition Studios is an internationally recognised multi-disciplinary environment for the advancement and understanding of practice in digital media and the arts. It provides nationally and internationally recognised artists, performers and technologists with a space in which to collaborate, experiment and create, as equal partners, in practice-based research. Within the University, our work complements and adds to a strong range of existing research and development in Digital Media and Creative Cultures across three faculties.
Data mining and advanced analytics
We are interested in data analytics, which is the analysis of large databases to find novel, commercially valuable and exploitable patterns. Our focus is on innovation in data science and analytics science, evidence-driven decision making research, and services in the broad-based analytics areas and domains. Our research involves developing cutting-edge theories and practices and solving real-life industry analytical problems in the following domains: Analytics Education and Training; Bioinformatics, Health and Medical Analytics; Business and Social Analytics; Fundamental Issues in Data and Analytics Science; Multimedia and New Media Analytics; and Smarter Living Technologies.
Decision support systems & e-service intelligence
We focus on theoretical and methodological questions arising in the field of decision support systems and e-service intelligence, but also actively commit to real-world problems of government and industry to improve business intelligence. The Decision Systems & e-Service Intelligence (DeSI) Laboratory’s research interests include data-driven and model-driven decision support systems, multi-criteria decision making, multi-level decision making, cognitive decision analysis, fuzzy decision making, fuzzy transfer learning, situation awareness, early warning systems, web intelligence and ontology, recommendation systems, concept drift, case-based reasoning, intelligent prediction systems, emergency management, risk analysis, and online negotiation.
Games
The Games Studio research group focuses on building tools, techniques and methods to create the next generation of games and its related technologies. Our research includes game analytics, strategic decision making, real-time games, player modelling, face-recognition, speech-recognition, serious games and gamification of everyday activities. We organise festivals and external speakers to enrich students' experiences and strengthen our industry relationships. We foster a collaborative and interdisciplinary research group and welcome new members.
Programming language design
We develop new programming styles and the languages and tools to make them real. Our programming language, bondi, bases all computation on a general, and powerful approach to pattern-matching derived from pattern calculus, a confluent and strongly-typed rewriting system. Our interests range from formal (including semantics of programming languages, type theory and term rewriting) to the intermediate (including interpreters, program analysis and optimisation, and abstract machines) with the rising temptation to build a decent compiler. Our current interest is to query functions in the same way that we query data structures.
Requirements engineering
The overall aim of research in the Requirements Engineering Lab is to enhance our understanding of the diverse and multi-disciplinary issues and challenges that people face in elicitation, modelling, specification, validation and management of requirements. These include business, user, system, functional, and non-functional requirements for software intensive systems. We are engaged in the rigorous design and development of sophisticated methodologies, techniques and tools, supporting both user and developer views, for technical, social and cognitive aspects of requirements analysis and modelling. Our research uses both qualitative and quantitative research methods in addressing open research questions within Requirements Engineering discipline.