Research Centre & Groups
Research activities in the Departments of Computer Science and Software Engineering take place in the following research centre and groups. Although many staff participate in projects across different groups we have arranged the descriptions below into these areas. In practice there is considerable overlap between the activities in the various groups.
Centre for Open Software Innovation
The Centre for Open Software Innovation (COSI) provides a focus for open software development at the University, promoting and supporting the principles of open development, and showcasing exemplars of open software. The Centre's research programme is directed by four goals:
- to inspire and extend open development practice in computer science
- to innovate systems, theories and tools to improve software processes and products
- to excel at core science theory and practice as the foundation for innovation
- to be community leaders at local, national and international levels through effective advocacy, communication and openness. COSI maintains a software repository that acts as an active work storage space allowing for comprehensive and systematic scientific testing that is lacking in most current software development. Read More
Cyber Security Group
The Cyber Security Researchers of Waikato (CROW) aims to return control of data to data owners, by focusing on research addressing data security from a user-centric perspective. With the emergence of cloud computing technologies and prevalent mobile device usage, we are witnessing the diminishing effectiveness of traditional cyber security approaches such as perimeter defence, intrusion detection and infrastructure hardening. Read More
Digital Library Group
The migration of information from paper to electronic media promises to change the whole nature of research and, in particular, the methods by which people locate information. The goal of the New Zealand Digital Library project is to explore the potential of internet based digital libraries. Our vision is to develop systems that automatically impose structure on fundamentally anarchic, uncatalogued, distributed repositories of information, thereby providing information consumers with effective tools to locate what they need and peruse it conveniently and comfortably.
Read More
Energy Informatics Group
Energy Informatics concerns the application of information technologies to improve the efficiency and effectiveness of energy utilisation, from source, through distribution, to consumption. Read More
Formal Methods Group
Established in 1998, this is the first Formal Methods laboratory in New Zealand. The work that goes on in this lab is based on the view that programming is at the heart of computer science. It is also based on the view that, as engineers and scientists, we should use the machinery of mathematics to model and reason about the systems that we build before we build them. Read More
Human-Computer Interaction Group
HCI is the noble face of computer science. The discipline is concerned with designing, implementing and evaluating human-computer interface technologies over an ever-expanding range of applications and environments, as computer technology becomes increasingly pervasive. It involves understanding how computer technology can better fit user needs, and provides theories and tools to assist developers in making useful and usable systems. Read More
Information Systems and Databases Group
Most of the computer applications you encounter today are in fact Information Systems, that means, systems that manage, store and deliver information to users. Examples are search engines like Google, ticket booking systems, or online stores. Exciting new kinds of applications that we look at in the ISDB group are mobile tourist information systems, memory-aid systems and systems that notify you about changes, eg, in web pages or online shops. Our latest projects are context-aware systems that deliver information to their users depending on a user's location, time of the day, task, or mood. Read More
Machine Learning Group
Machine learning is concerned with the task of automatically extracting useful information from data. The aim is to identify patterns that can be used to understand the domain from which the data was collected and to make predictions. Read More