Carla Ewels is a Lecturer in statistics/data sciences at James Cook University. She received her doctoral in statistics from the Queensland University of Technology supervised by the Distinguished Professor Kerrie Mengersen. Carla has strong interests in statistical modelling and methods, particularly in the Bayeisan framework. These include, but are not limited to, modelling of complex systems, Bayesian temporal and spatial models, model comparisons, classification, clustering, analysis of big data and Markov Chain Monte Carlo methods. She is especially interested in applying statistics to real problems. To date, she has worked in the field of marine and medical research, genetics, agriculture and fisheries.

  • MA2405: Advanced Statistical Modelling (Level 2; CNS & TSV)
  • MA3405: Statistical Data Mining for Big Data (Level 3; CNS & TSV)
  • MA3831: Natural Language Processing, Web Scraping and Large Data Processing (Level 3; CNS & TSV)
  • MA5405: Data Mining (Level 5; TSV)
  • MA5821: Visual Analytics for Data Scientists using SAS (Level 5; CNS & ONL)
  • MA5832: Data Mining and Machine Learning (Level 5; CNS & ONL)
  • SC2209: Quantitative Methods in Science-Advanced (Level 2; CNS & TSV)
  • SC5200: Career Planning (Level 5; CNS & TSV)
  • Statistical modelling and methods
  • Bayesian statistics
  • Real world data
  • Uncertainty
  • Data sciences
  • Model and variable selection
  • Statistics
Research Disciplines

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles
Conference Papers
Current Funding

Current and recent Research Funding to JCU is shown by funding source and project.

CSIRO - Al for Missions Postgraduate Program

AI/ML-based risk prediction for zoonotic spillover

Indicative Funding
$164,250 over 3 years
More than 70 per cent of emerging infectious diseases are transmitted from animals to humans, and their incidence has tripled over the past 50 years. Predicting future spillover risks are increasingly crucial to human health and wellbeing, and economic stability. This project focuses on developing computationally efficient AI/ML algorithms to leverage large spatiotemporal environmental, human, and animal data sets for the purpose of predicting spillover risk. The main objectives of this project are to identify ? key reservoir hosts that increase the chance of zoonotic spillovers, ? the pathogens that are most likely to emerge, ? geographic origins of a potential future pandemic, and ? use process-based approaches to supplement and help correct biases of the data-based AI/ML approaches. We expect these models and results to contribute to the early warning and decision support systems on our paths to impact.
Sania Qureshi, Roslyn Hickson, Maryam Golchin, Carla Ewels, Andrew Hoskins and Anjana Karawita (College of Public Health, Medical & Vet Sciences and College of Science & Engineering)
Biosecurity; Emerging infectious diseases; Zoonoses; Machine learning; Artificial Intelligence

Australian Research Council - Linkage - Industrial Transformation Research Hubs

ARC Research Hub for Supercharging Tropical Aquaculture Through Genetic Solutions

Indicative Funding
$4,996,503 over 4 years, in partnership with Australian Genome Research Facility ($150,000); Cygnet Bay Pearls PL ($500,000); Mainstream Aquaculture ($500,000); Sea Forest Pty Ltd ($500,000) and THE COMPANY ONE PTY LTD ($500,000)
This project aims to integrate cutting edge genetic and genomic approaches into innovative aquaculture enterprises that farm in tropical northern Australia. It will deliver the requisite genetic knowledge to instigate world-leading and highly productive breeding programs for five species (barramundi, pearl oyster, prawn, grouper and marine seaweed), along with a novel understanding of the genetic basis of disease resistance and how the production environment interfaces with the bacterial microbiome, pathogens and water quality to cause disease. It will increase Australia's capacity to deliver advanced genetics outcomes to the aquaculture sector, while increasing productivity, international competitiveness, and lowered risk due to disease.
Dean Jerry, Kyall Zenger, Benjamin Hayes, Rocky de Nys, David Bourne, Andreas Lopata, Ron White, Jan Strugnell, Chaoshu Zeng, Kelly Condon, Mostafa Rahimi Azghadi, Ira Cooke, Leo Nankervis and Carla Ewels (College of Science & Engineering, The University of Queensland, College of Public Health and Medical & Vet Sciences)
Selective Breeding; Genomics; Aquaculture

Great Barrier Reef Foundation - Crown-of-Thorns Control Innovation Program (CCIP)

Empirical decision support

Indicative Funding
$147,000 over 4 years
Innovation program on CoTS control in the GBR. I am involved in the subject program, empirical decision support. In this part of program, our goal is to deliver immediate and ongoing decision support using available data, this includes analysing program data to enhance the efficiency of on water operation and the development of a new early warning system that leverages data from field and modelled data.
Carla Ewels (College of Science & Engineering)
Crown of thorn starfish; Early earning system; Empirical decision support

Great Barrier Reef Foundation - Crown-of-Thorns Control Innovation Program (CCIP)

Crown-of-thorns starfish control innovation program ? Feasibility and Design Phase (Phase 1)

Indicative Funding
$346,700 over 1 year
Recognising that manual control of COTS during outbreaks is not, on its own, an ideal long-term solution, new efforts were launched in 2016 to develop an Integrated Pest Management approach for COTS (as part of the National Environmental Science Program), led by CSIRO and involving numerous partners. This approach relies on understanding COTS distribution, movement and population dynamics, targeting critical locations and exploring new and more effective control methods. This involves both improving the efficiency and effectiveness of the current methods while also focusing efforts to better understand and manage the pre-conditioning and initiation of outbreaks. A Feasibility and Design Phase (Phase 1) is focused on assessing the feasibility (technical, social and regulatory) and modelling the benefit (impact) at scale of a broad range of possible improvements and interventions. Applying a transparent and consistent scientific framework, this Phase will lead to recommendations on priority areas that should be further investigated and developed
Morgan Pratchett, Damien Burrows, Ciemon Caballes, Stewart Lockie and Carla Ewels (Research Division, College of Science & Engineering and Cairns Institute)
Coral Reef; acanthaster spp; Management; Disturbance; Monitoring

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

  • Dynamic and stochastic vehicle routing for autonomous weed control. (PhD , Secondary Advisor)
  • AI/ML - based risk prediction for Zoonotic Spillover (PhD , Secondary Advisor)
  • Using Weather Radars to Inform Data-Driven Irrigation Practices (Masters , Secondary Advisor)
  • The development of a computational model using data science approaches to predict frailty and health deficits in the elderly living in institutional care to better support the aged care system. (PhD , Primary Advisor)
  • Isolation, Identification and Molecular Characterization of Gram-negative Antibiotic-resistant Bacteria from Captive and Stranding Green Sea Turtles in Thailand (Masters , Secondary Advisor)
  • How intraspecific variation shapes the climates sensitivities of species (PhD , Secondary Advisor)

The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.

  • 5+ collaborations
  • 4 collaborations
  • 3 collaborations
  • 2 collaborations
  • 1 collaboration
  • Indicates the Tropics (Torrid Zone)

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