University of Otago was founded in 1869 as New Zealand’s first university. It has over 21,000 students. Between 1874 and 1961 the University of Otago was a part of the University of New Zealand, and issued degrees in its name. It is divided into four divisions: Humanities, Health Sciences, Sciences, and Business. The Department of Computer Science, which is in the Division of Sciences, was founded in 1983. It has five research groups: artificial intelligence, computer theory, graphics and vision, and systems.
Research Group Background
The Systems Research Group was founded in 2000. We explore many aspects of parallel and distributed computing, computer networks, and green computing. We have a wide range of projects on wireless sensor networks, multicore computing, distributed event-based systems, brain-computer interface, computational neuroscience, e-Research, ad-hoc and mesh networks, cyber-physical systems, parallel and distributed algorithms, transactional memory, parallel programming models and environments, energy models and energy saving in parallel/distributed systems, embedded systems, mobility management and QoS in mobile networks, and target localization. We have expertise from many areas of computer science and engineering including operating systems, computer architectures, signal processing, machine learning algorithms, systems analysis, data communications, network protocols, and system modeling and simulation.
On-going projects include large-scale 3D reconstruction with 2D images through parallel and distributed computing, power modeling in parallel and distributed computing, resource allocation in optical network on chip, indoor localization with wireless networks, wireless body sensor networks, signal processing for brain-computer interface and neuroscience.
Major Interest in Action Scientific Topics
The expertise of the Systems Research Group will allow the group to contribute to WG2 (programming models and runtimes), WG5 (energy efficiency) and WG6 (applications). Also given our more than 20 years of experiences in parallel and distributed computing, we are interested in contributing to WG1 (state of the art and continuous learning in ultra scale computing systems) and WG3 (resilience of applications and runtime environments) if the hardware platform and student resources are available.