Big Data Lab
The Swinburne Big Data Lab focuses on research and development in big data preparation and curation, including data management, databases, scalable scheduling and distribution, cloud computing, data security and privacy.
Our examination of big data analytics includes predictive analytics and decision making, people analytics, deep learning, machine learning and computer vision, and visual analytics.
We also investigate big data visualisation and big data access for applications (such as business, transport, logistics, education and health).
Our experts are investigating innovative ways to identify, extract and integrate intelligence from big data to enable organisations to discover and act on opportunities to improve their productivity, economic growth and sustainability.
Professor Jinjun Chen has a PhD in IT, Master of Engineering and a Bachelor of Science (Applied Mathematics). His research expertise includes big data, data science, cloud computing, scalable software systems, big data security and privacy-related areas. He has achieved numerous high quality publications, competitive research grants and intensive industry engagement in those areas.
- Large-scale big data capturing, preparation/curation, storage and scheduling
- Big data application workflow and process management
- Large-scale big data analytics, predictive analytics, casual associate rules mining
- Big data systems and infrastructure, e.g. cloud computing, Hadoop/Spark
- Big data security and privacy.