Swinburne launches Data Science Research Institute
ALEKSANDAR SUBIC: We live in the age of digital disruption. And data is at the heart of that disruption. It drives and it enables almost all elements of our ecosystem and industry in business. For this reason, digitalization is at the heart of the Swinburne risk generation strategy.
TIMOS SELLIS: The Institute brings together Swinburne's expertise in big data and data analytics, in machine learning, statistics, computational science and visualization, and focuses on addressing questions of national importance.
ALEKSANDAR SUBIC: We are seeing an amazing growth in risk generation activity, and outcomes which ultimately we wish to create impact our day outside of the University.
AMY SHI-NASH: So from the industry point of view, there really couldn't be a better time for data science professionals. We are in a new era. We are in the industrialization of the data science.
RAGHU RAMAKRISHNAN: It's a pleasure to be here at Swinburne. I've known Timos Sellis for over 30 years. We've been colleagues in the field of data, databases, data science over many, many years. And I'm excited to see him here at Swinburne, which has a tradition of interdisciplinary work, a model of centres that bring together leaders in industry with the resources for university to work at the intersection of really practical things and take academic research and translate it into real progress of the work.
LINDA KRISTJANSON: The Institute will leverage the capabilities of data science across the whole university, so this is a whole of University initiative. And that's what gives it the power and the excitement.
TIMOS SELLIS: So the Data Science Institute will focus on four core research programs; new data science methodologies for scientific discovery, core data science architectures and tools, analytics for digital disruption in various sectors, and novel data science platforms such as the data incubator.
ALEKSANDAR SUBIC: These are really exciting times at Swinburne. With the launch of our risk generation strategy last year, we've mobilized all of our risk generation assets and capacities across the campus.
RAGHU RAMAKRISHNAN: Hopefully, the insights you get from interpreting data will illuminate different fields. To accomplish this, you need to think of data as part of other things. So here you seem to have that. You seem to have that vision where you don't just have this one Data Science Institute. It's part of institutes in manufacturing, and healthcare, and social sciences. And that's, I think, the right way to think about this.