Intelligent Data Analytics Lab
The Intelligent Data Analytics Lab focuses on the research and applications of artificial intelligence techniques for tackling versatile real-world data analysis tasks across various fields. The Lab aims to facilitate the data-to-discovery or data-to-decision process, especially in the context of big data.
In the era of big data, data analytics underpins the data-intensive research that responds to industrial challenges. Artificial intelligence (AI) has developed into the most powerful data analytics technology in recent years, leading to remarkable breakthroughs in many fields.
These breakthroughs are benefiting industrial sectors as varied as information and communications technology (ICT), finance, health, transportation and manufacturing.
The Intelligent Data Analytics Lab leverages the combined power of artificial intelligence, big data and high-performance computing to deliver accurate, fast and robust data analysis solutions needed by industrial and governmental sectors as well as academia.
Swinburne’s intelligent data analytics experts are investigating innovative ways to identify, extract and integrate intelligence from data to enable organisations to act on opportunities to improve their productivity, economic growth and sustainability.
The Intelligent Data Analytics Lab’s major research capabilities include:
machine learning (particularly deep learning, ensemble learning and transfer learning)
optimisation (particularly data-driven evolutionary optimisation)
collaborative learning and optimisation (i.e., the synergy of machine learning and optimisation)
distributed machine learning and distributed optimisation based on high-performance computing facilities with hybrid GPU-CPU architectures
big data analytics (particularly predictive and prescriptive analytics)
computer vision, image processing and video analytics
text mining and analytics
The Intelligent Data Analytics Lab has access to Swinburne supercomputer OzSTAR, which is one of the most powerful high-performance computing facilities in Australia.
4140 SkyLake cores at 2.3Ghz across 107 standard compute and 8 data crunching nodes
230 NVIDIA Tesla P100 12 GB GPUs
272 Intel Xeon Phi cores at 1.6Ghz across 4 C6320pKNL nodes
High-speed and low-latency network fabric able to move data across each building block at over 100Gbps with various features to ensure reliability and traffic flow
5 petabyte of usable storage via the Lustre ZFS file system at 30GB/s throughput.
It can provide sufficient computational horsepower to enable computationally intensive data analytics, especially for handling big data.
Intelligent Data Analytics Lab booklet
CRC funds Swinburne Supply Chain Project to get milk from farm to fridge fasterSwinburne will lead a research project to develop technology that will enhance the productivity and competitiveness of Australia’s dairy industryThursday 15 August 2019
Analysing data to predict the evolution of technologiesA Swinburne team is analysing text data from Australia’s patent office to predict the evolution of technologies.Tuesday 30 April 2019
Swinburne and Microsoft employability pilotIn an employability skills program pilot, Microsoft trialled workshops at Swinburne to help students enhance their employability prospects.Monday 15 April 2019
Swinburne researchers use blockchain technology to prevent art forgeryA Swinburne cyber security expert is adapting Blockchain Technology to vouch for authenticity of art.Wednesday 10 April 2019
Leading the way in Industry 4.0The world is in the midst of a fourth industrial revolution (Industry 4.0).Thursday 14 March 2019
Contact the Intelligent Data Analytics Lab team
For all general enquires, or to enquire about collaborating or partnering with the Intelligent Data Analytics team, please contact Associate Professor Kai Qin, Director of the Intelligent Data Analytics Lab on +61 3 9214 3766 or via firstname.lastname@example.org.