ORCA Students

Thye Way Phua (CROW) - PhD Candidate - Cyber Security

Redesigning Files to Embed Concise Provenance Metadata
Data provenance in cloud storage is a solution to enable users to regain control and knowledge over their own data. Existing approach to tracking data provenance fails to address the problem completely as the provenance data is stored separately from the data, while the vendor still has complete control over the provenance logs. The research aim is to redesign files to embed concise provenance metadata, assuring correctness and completeness in provenance data.

Stephen Burroughs - PhD Candidate

Chris Chew (CROW) - PhD Candidate - Cyber Security

Chris Anderson - PhD Candidate

Mark Rodrigues - PhD Candidate (Machine Learning)

Vance Farrow - PhD Candidate (WAIRAS)

Master's

Tim Oliver - Master's of Science (Research)

eBike Drive Control Systems
Tim is currently the Creative Director of Corax Audio Labs where he helps design and build pro audio and Hi-Fi equipment. He has recently graduated with a Bachelor of Engineering with Honours in Electronic Engineering and is currently doing a Master of Science (Research) in Computer Science. His current field of research is into self-adaptive systems for eBike drive control systems.

Tamahau Brown - Master's of Science (Research)

Leandro Gomes De Oliveira - Master's of Science (Research)

Glyn Webster - Master's of Science (Research)

Kushan Fernando - Master's of Science (Research)

Jarod Govers - MCS

Shaan Nagra - Master's of Science (Research)

Bachelor's with Honours

Priyank Vyas - Bachelor of Computing and Mathematical Sciences

JuryRoom: How do we achieve consensus
JuryRoom is a system developed at Waikato, in collaboration with the University of Maryland, that provides a platform for individuals to conduct discussions on a given topic and we observe whether, at the end of the discussion, consensus is achieved on a viewpoint about said topic. It is of interest to see if we can perform an analysis that can characterize discussions that seek agreement and identify properties that distinguish between those that succeed or fail at reaching consensus. The system may also support cross-culture and interlingual studies. This project seeks to use Natural Language Processing, computational linguistics and machine learning techniques to identify certain sentence structures or keywords that can be distinctly identified to affect a person into reaching consensus. We ultimately aim to provide the JuryRoom platform with an analytical backend that can be used by researchers in the future to perform similar analyses on the discussion data.

Daniel Wheeler - Computing and Mathematical Sciences

Hunter Cavers (CROW) -Engineering