Biography

Leader of IT solutions and data science at PAG. He helps companies and departments transform by deploying digital and data analytics solutions, ensuring that the end to end product from foundational mathematics to customer interfaces are of the highest quality.

In his nearly 20 years in data analytics, Chris has worked across fields including academia, banking, environmetrics, essential services, utilities, econometrics, community disadvantage, IoT, sports, health, retail, operations research, meat science, agriculture, pest management and asbestos detection.

Examples of Chris’ recent client and product work include:

• SchedulOpt:  A world leading sports scheduling platform with numerous clients across Australia and Northern America.
• Racing Queensland:  PAG delivered a scenario engine, which accurately forecasts turnover at the meet level, for several months ahead of time. The platform facilitates improved planning through data driven decisions.
• Asbestos detection:  PAG developed an asbestos detection engine, which works in conjunction with a microwave sensor, to predict asbestos in non-disturbed wall sheeting, with an accuracy of above 99%. The next closest known competitor is a university group that achieves near 90% accuracy. Unlike PAG’s device, their device requires dangerous asbestos fibres to be exposed.
• Prostate Cancer:  PAG are working with Queensland Health in building a AI assisted platform for prostate cancer. The image classification methods developed by PAG can currently segment the images, with an accuracy of 99.97%.
• SEW:  PAG delivered an anomaly detection system, which was designed to detected blockages in the sewage systems. The system learns in real time and is deployed across the south eastern suburbs of Melbourne.