Data Science Research Institute
The Swinburne Data Science Research Institute leads the data-to-discovery pathway for data-intensive research (in biology, physics, astronomy, economics and the social sciences) and grand challenges in industry.
The Institute leads the vanguard of data science, the emerging academic inter-discipline that marries the physical sciences with statistics and computer science.
Our core business is developing cutting-edge methodologies for handling and analysing large and complex data sets.
We will provide a creative solutions shop, where we develop novel data science methodologies, and a conduit between research and industry. We will achieve this in the following three ways.
New data science for scientific discovery
We will create methodologies for handling and analysing large and complex data sets to facilitate the data-to-discovery process. Our focus will be applications of data-driven computing in various scientific domains, such as biology, physics, astronomy, economics and social sciences.
Novel data science platforms
We are developing a data incubator for use by researchers and industry partners to improve data quality, create predictive insight and produce consumable information.
Our data incubator will offer a comprehensive set of big data services that leverage best-of-breed tools and the resource expertise of Swinburne and industry.
Core data science research
We specialise in data management, machine learning, statistics, data visualisation and programming environments (e.g. scale simulation, optimisation, machine learning) as well as scalable hardware and software architectures.
Our scientists’ expertise spans critical aspects of computational science. We work collaboratively with research groups at Swinburne and industry partners. The objectives of the Institute dovetail with the interests of, and draw upon expertise from, several of Swinburne’s established research centres, including the Centres for Astrophysics and Supercomputing, Micro-Photonics, Quantum and Optical Science, and Transformative Innovation as well as research groups within schools.
Unlike any other area of contemporary research, data scientists are highly sought after by industry to address their big data needs. By providing research scale, the Institute will be able to support a large corps of talented data scientists while also providing a stable, quality resource for shorter-term project work. The Institute will be the natural choice for external partnerships with these projects.
Meet the Institute Director
Professor Timos Sellis is the Foundation Director of the Data Science Institute. Up until 2012, Timos was Director of the Institute for Management of Information Systems and Professor at the National Technical University of Athens. More recently, he was Director of Big Data Lab at RMIT University. He has a significant international research reputation in big data, data analytics, data integration, and spatio-temporal database systems.