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Announcing our second round of data fellowships
Announcing our second round of data
fellowships
8 June 2018
Tags:
Data (/taxonomy/term/17)
Seven more data specialists are taking up our highly coveted three-month fellowship
placements. They’ll develop solutions to data-related problems and help to improve
government services.
Caption: Our seven latest data fellows. Top row left to right: Todd Campbell, Gabriella Duddy,
Dipangar Kundu, Daniel Merkas. Bottom row left to right: Jack Xu, Rakhesh Devadas, Patrick
Drake-Brockman
We’re pleased to announce our second round of data fellows for 2017–18. We’ve picked seven
talented people to take part in three-month placements under our Data Fellowship Program
(/node/320).
We’ve awarded the fellowships to high-performing data specialists in the Australian Public
Service. During their placements they work with the
CSIRO (https://www.csiro.au/)’s data-
innovation group Data61 (https://www.data61.csiro.au/en/Who-we-are) and will develop
solutions for data-related problems or opportunities.
The fellowships give public service staff the chance to step outside their day jobs and create
prototypes that improve or completely redesign our approach to real-life problems.
Participants come from a variety of government agencies. These fellowships give them access
to mentoring, skills development and new and emerging technologies and techniques.
Here are our seven new data fellows and the projects they’re working on between now and
mid-October 2018:
Checking financial condition reports
Todd Campbell
Australian Prudential Regulation Authority
(http://www.apra.gov.au/Pages/default.aspx)
Todd is looking at how to use text analytics to help identify insights and risks
in prudential supervisory reviews of insurance companies’ financial condition reports. He’s also
looking at identifying efficiencies and compiling an overview of the industry to assist
supervisors.
These documents are currently reviewed manually to identify issues and feed into other risk
assessments. Specialist teams also review the documents to help supervisors, and more
systematic analysis could assist this process.
Todd is responsible for delivering an Innovation Centre Lab for the Australian Prudential
Regulation Authority.
The goal of the lab is to test modern analytics approaches that could provide new insights and
support decisions relating to the authority’s prudential supervision role.
Automating land-use delineation
Rakhesh Devadas
Australian Bureau of Agricultural and Resource Economics and Sciences
(http://www.agriculture.gov.au/abares) (Department of Agriculture and Water
Resources)
Rakhesh is developing techniques to automate the way agricultural land uses are mapped at a
national scale.
His project will also improve methods for building the Land Use of Australia data series for
understanding current and long-term changes in Australian land use.
He’s doing this by developing advanced geospatial data-analysis and modelling techniques.
These techniques will combine satellite-derived information and various national datasets.
Rakhesh has post-graduate qualifications in agricultural economics and a doctorate in spatial
data applications.
His 16 years’ of professional experience include implementing operational projects for the
NSW and Queensland state governments and research projects involving satellite time-series
data at RMIT University in Melbourne and University of Technology Sydney.
Analysing government buying patterns
Patrick Drake-Brockman
Digital Transformation Agency (https://beta.dta.gov.au/)
Patrick’s project will provide data about the way government agencies buy
products and services and the sellers they buy from.
He’s using longitudinal network analysis to look at datasets held by AusTender, the website
where many contract details are posted. This analysis will show the effects policy changes have
on forming networks between government agencies and sellers.
Patrick is a senior adviser in the Digital Transformation Agency’s investment office, providing
advice to the government on ICT procurement proposals.
He’s spent 19 years in the Australian Government in roles including ministerial ICT support,
critical infrastructure policy and national security information sharing policy.
Detecting non-compliance in regulatory schemes
Gabriella Duddy
Clean Energy Regulator (http://www.cleanenergyregulator.gov.au/)
Gabriella is using machine learning to help the Clean Energy Regulator (CER)
detect non-compliance in its regulatory schemes.
She’s developing a process for the Small-Scale Renewable Energy Scheme to help the CER to
use its resources more efficiently and strengthen the integrity of Australia’s Renewable Energy
Target.
Gabriella has worked across the CER’s intelligence and analytics functions, helping to develop
the agency’s approach to increasing data capability.
She’s in her final semester of a Master of Energy Change at the Australian National University
in Canberra.
Targeting biosecurity risks at airports
Dipangkar Kundu
Department of Agriculture and Water Resources
(http://www.agriculture.gov.au/)
Dipangkar is developing an empirical model for identifying and targeting
potential non-compliance biosecurity risks at Australian airports.
His model will help to find risk patterns and identify international travellers who carry a higher
biosecurity risk.
Dipangkar is a senior data analyst at the Department of Agriculture and Water Resources,
where he was honoured with the Secretary Award of Achievement for his contribution to
biosecurity risk profiling.
He has a PhD in computational hydrology from the University of Sydney.
Improving survey accuracy
Daniel Merkas
Australian Bureau of Statistics (http://www.abs.gov.au/)
Daniel is developing machine-learning models to improve the quality and
efficiency of the address register held by the Australian Bureau of Statistics.
The register contains more than 10 million addresses and helps to improve surveys and link
datasets to inform Australia’s important decisions.
He’ll use machine-learning algorithms to automate decisions that currently need people to
carry them out and are resource-intensive.
Daniel is a statistician in the bureau’s address register unit and is studying for a Master of
Science (Applied Statistics) at Swinburne University.
Simulation model for call-centre activities
Jack Xu
Department of Human Services (https://www.humanservices.gov.au/)
Jack is building a simulation model that will replicate the day-to-day
telephone activities of the Department of Human Services.
He plans to show information including customer wait times, number of
transferred calls, busy signals, level of staff occupancy and more. Jack’s model
will enable his team to answer important business questions with more
confidence than ever before.
Jack is a data analyst whose job is to look for ways DHS operational staff can be more efficient
in their work. This includes helping to ensure the department achieves its telephone and claims
processing deliverables.
He previously worked at analytics software firm SAS Institute and holds a Bachelor of Actuarial
Studies.
Find out more about our Data Fellowship Program (/node/320).
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