Tomasz Bednarz is an A/Professor and Director of Visualisation at the EPICentre UNSW and Team Leader at CSIRO's Data61 (Big Data Visualisation and Analytics Team). He is also linked with the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) and holds Adjunct positions at the QUT (Mathematical Sciences), University of Sydney (Design Lab) and University of South Australia (School of IT and Math Sciences). He has done his doctorate and masters in computational science area, and is currently undertaking MBA-Executive study at the ACU. Over last couple of years at he has been involved in wide range of projects in area of immersive visualisation, human-computer interaction, computational imaging and visualisation, multi-sensors assimilation. He led cloud-based imaging project that received merit Queensland's iAward in 2015 (http://cloudimaging.net.au). He has been leading project Platform for Big Data Analytics and Visual Analytics, connecting data analytics, statistical modelling, image analytics, machine learning, visualisation into one stack of reusable solutions running on the CSIRO infrastructure. His broad range of expertise is evidenced by the quality and number of publications, http://www.researcherid.com/rid/A-7376-2011.
ACEMS Deputy Director Kerrie Mengersen is leading a team of researchers to try to save the jaguar population in Peru. Her project combines the use of statistics, mathematics, and virtual reality technology to help leaders make informed decisions about the threatened species, and the land it depends on.
Investigation and development of virtual log models for Southern Pines will be based on analysis of data from the cores, peeled billets and approximately 60 sawn logs. We plan to predict log and stem wood properties from the breast height cores taken in the field study. Following this, applied mathematics will be used to investigate the processing of these virtual logs and predict properties for the virtual boards ‘sawn’ from these logs.
Enormous effort is invested in monitoring the Great Barrier Reef (GBR), but data collection is currently fragmented over dozens of publicly and privately funded organisations, with data collected using different methods and for different purposes. As a result, the data are rarely analysed together.
Lagerstrom, R., Arzhaeva Y., Szul P., Obst O., Power R., Robinson B., et al.
(2016). Image classification to support emergency situation awareness. Frontiers in Robotics and AI. 3, doi: 10.3389/frobt.2016.00054