Areas of software research interest
Data sciences and knowledge discovery
The Data Sciences & Knowledge Discovery Research Lab (the Smart Lab) aims to foster both theoretical and practical innovation in areas of machine learning, data mining and knowledge discovery, data sciences, behaviour informatics, and agent-mining interaction & integration. We also commit to real-world business problems and deliverables by scrutinising data agility, discovering actionable knowledge, and disclosing business intelligence for smart business decisions.
Decision systems and e-Service intelligence
Electronic Services (e-services) offer great opportunities and challenges for many areas, such as business, commerce, marketing, finance, and education. It involves various online service delivery systems and applications including e-government, e-commerce, e-business, and e-learning. E-services is currently developing its next stage for emphasizing intelligent presentation of web content, intelligent online services, personalized support, and direct user participation in organizational decision-making processes. E-service intelligence, an integration of intelligence technologies and e-services, has been right now identified as a new direction and next stage of e-services. Intelligent online services will provide with much higher quality information, personalized recommendation, intelligent decision support, and more integrated seamless link services. Moreover, they will make e-service evolve into knowledge management services and become adaptive, personalized, proactive and accessible from a broader variety of devices.
Innovation and technology research
Research topics of interest in the Innovation and Enterprise Research Laboratory for 2009 and 2010 include, but are not limited to:
- Innovation, IT & the Law
- Business Strategy
- Cognitive Systems
- Decision Making and Risk Management
- Global Business
- Strategic Management
- Knowledge Management
- Logic-based Artificial Intelligence
- Strategic Business Innovation & Collaboration
- Innovation Management
Interaction design and work practice
Interaction design is an emerging area of design research and practice that is concerned with those aspects of the design of interactive technology that shape people's experience when they use the technology. It is the design of the potentials for possible action by real, living people when they use information and communications technologies to support, mediate and/or enable their activities in some way.
Our starting point for the design of any technology for human use is the recognition that all human action is embodied, situated and social. An understanding of actual human practice is basic to our research and this is reflected in the design of our projects and in the interdisciplinary approaches, techniques and methodologies we use. This is the lab where human-computer interaction (HCI) and usability design research is done.
The overall aim of requirements engineering research at UTS is to provide a detailed and rigorous understanding of the diverse and multi-disciplinary issues and challenges that people face in elicitation, modelling, specification, validation and management of requirements. Also, to develop sophisticated methodologies, techniques and tools, supporting both user and developer views, which embrace technical and cognitive aspects of both domain and user modelling in requirements engineering.
We are interested in novel methodologies, methods, frameworks, algorithms and models for mining new data types and pattern types, including but not limited to Activity Mining, Combined Mining, Domain Driven Data Mining, Dynamic Mining, Innovative Associations, Kernel Methods, Multi-Data Source Discovery, Missing Data Imputation, Support Vector Machine, Sequence Mining, Multi-Time Series, and Visual Pattern Analysis in data such as social security data, market microstructure data, sequential and time-series data.
Creativity and Cognition
The nature of individual and collaborative creative processes. Changes to practice and modes of learning. Research into the psychological and social processes of creativity and the impact on them of digital media developments.
Algorithmic and evolutionary art. Media integration. Research into generative art, both visual and sonic, and into the cellular automata and logics that enable their creation.
Virtual, augmented and physical spaces and cybernetic art systems involving physical participation and interaction. Technology enhanced and enabled performance. Research into interactive art systems in physical spaces and distributed interactive spaces and into the technology of such systems.
Digital and interactive new media. Internet enabled and enhanced creative communities. Computer game development as entertainment, training, visualisation and interactive art. Research into emerging digital technologies and their impact for creative practice and creative communities.
Object technology and applications
Today's businesses, large and small, rely heavily on computers and computer programs (software). Highly reliable business systems are based on a still relatively new approach to developing software known as object technology. A well-defined strategy for using object technology has been shown to give competitive advantage in a wide range of businesses, including airline reservations, banking, stock markets and freight handling.
The knowledge infrastructure lab aims to use knowledge as the infrastructure to support decision making. We do that in a number of ways some of which are using agent technology to support e-Markets; by assisting clinicians and biologists in cancer diagnosis and treatment; and in development of new languages to support pattern matching. Our work includes the Bio group that uses knowledge to support decisions in medical and the biological domain, the e-Markets Group that focuses on supporting e-Markets and financial decision making and the Languages group that focuses on supporting smart data mining and knowledge representation through language design and type theory.