Melbourne Data Science Week - 24-27th Sept 2018

Borislav Savkovic

Borislav Savkovic



Boris is currently the data science lead at Intelematics (Intelematics is a leading provider of connected mobility services across Australia, the US and the EU, with a reach of more than 100 million auto-club members around the world). Prior to joining Intelematics, Boris was the lead data scientist at BuildingIQ (venture-backed by Siemens and Schneider Electric) where he led the development of machine learning algorithms for the optimisation of energy usage in large-scale buildings (skyscrapers, hospitals etc), from the early stage through to a successful IPO. Prior to that he worked as a biostatistician in the pharmaceutical industry with Calimmune (spinoff from The California Institute of Technology), where he was responsible for statistical modelling and analysis relating to gene therapy treatments of HIV/AIDS and immune disorder diseases. He has also acted as a private statistical consultant to the private and government/research sectors. Boris holds a PhD in Applied Mathematics from The University of New South Wales (UNSW) and a BE (Hons 1) in Engineering also from UNSW. Boris’ experience spans the Australian, US and European markets.

Connected vehicle, connected infrastructure and predictive analytics in the traffic/automotive space: data science on the IoT front line

The application of streaming and real-time data analytics for automotive and traffic applications is gaining traction around the world. Underpinning this shift is the increased availability of streaming data from vehicles, connected devices and also from the underlying transport infrastructure. In addition to the streaming nature of the data, these rich data feeds also constitute a highly distributed (spatial extent) and highly dynamic (temporal extent) IoT grid. These considerations present enormous challenges but also many opportunities.

In this talk I will highlight some exciting and emerging trends in relation to connected vehicles, the connected infrastructure and other applications of data science in the traffic/automotive space. The emphasis will be on the critical role that data science has to play in this evolving segment and the many opportunities that this presents in terms of creating the smart and sustainable city of tomorrow.