About
Teaching
  • BU3102: Multidisciplinary Project (Level 3; CNS)
  • CP2408: Design Thinking and Creative IT Industries (Level 2; TSV)
  • CP3101: Professional Internship (Level 3; CNS & TSV)
  • CP3102: Multidisciplinary Project (Level 3; CNS & TSV)
  • CP3103: Independent Project (Level 3; CNS & TSV)
  • CP3405: Design Thinking and Project Management (Level 3; CNS & TSV)
  • CP3406: Mobile Computing (Level 3; CNS & TSV)
  • CP5307: Advanced Mobile Technology (Level 5; CNS & TSV)
Research Disciplines
Socio-Economic Objectives
Honours
Awards
  • 2017 - CSIRO STEM Professional
  • 2017 - Advance Queensland Community Digital Champion
Publications

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
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ResearchOnline@JCU stores 34+ research outputs authored by Dr Jason Holdsworth from 2004 onwards.

Current Funding

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

Fisheries Research & Development Corporation - Annual Competitive Round

Application of a machine learning approach for effective stock management of abalone

Indicative Funding
$115,649 over 3 years
Summary
Determining the number and size distribution of abalone present at various stages of production is critical information for effective stock management. Currently the Australian abalone aquaculture industry spends in the order of $25,000 per annum, per farm, gathering this information by hand. However, the resulting data is of mediocre quality, is limited in its scope, and collecting the data causes stress to the animals which can compromise growth and survival. Automated counting and measuring of abalone will increase farm efficiency and productivity in the short term and, in the longer term, will provide an advanced platform for further R&D improvements. Artificial intelligence and machine learning has now matured to a point that accurately counting and measuring abalone is possible using this approach. This project would involve the development, training and validation of a machine learning model to identify, segment and measure quantitative abalone traits in production systems, and render the product data to be accessible and applicable for farmers.
Investigators
Jan Strugnell, Marcus Sheaves, Carlo Mattone, Ickjai Lee, Joanne Lee, Jason Holdsworth and Art (Hemmaphan) Suwanwiwat (College of Science & Engineering)
Keywords
Abalone (Haliotidae); Machine Learning

World Wide Fund for Nature - Contract Research

From Coastal Communities to Cloud Communities ? New Application and Artificial Intelligence to Monitor Fish Stocks Using Photos ? Application Development

Indicative Funding
$53,100 over 2 years
Summary
The Project aims at develop an artificial intelligence capable to autonomously identify fish species and number from images collected at fish markets in remote location, so that effective catch rate can be evaluated and management policies can be developed.
Investigators
Marcus Sheaves, Carlo Mattone, Michael Bradley, Joanne Lee, Jason Holdsworth, Art (Hemmaphan) Suwanwiwat and Ickjai Lee (College of Science & Engineering)
Keywords
Artificial Intelligence; Phone App; Caught Fish; Catch Rate
Supervision

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.

Current
  • An Autonomous Tool to Produce Prototype Neural Networks for Deep Learning (PhD , Secondary Advisor)
  • Efficient Semantic Segmentation using Deep Learning. (PhD , Secondary Advisor)
  • Development of high-level programming tools to improve the robustness of Internet of Things networks. (PhD , Secondary Advisor)
  • Leveraging E-Learning in educational institutions (PhD , Primary Advisor)
  • Exploring the Effects of Synchronous, Asynchronous and Blended Learning Approaches on Academic Learning Behaviours for Visual, Auditory and Kinaesthetic Learners (PhD , Primary Advisor)
  • Designing physical interface for application of augmented reality in toddler toys (Masters , Secondary Advisor)
  • Investigating the Pedagogical Efficacy of Current Tools used in the Teaching of Coding to different age groups (Masters , Secondary Advisor)
Completed
Data

These are the most recent metadata records associated with this researcher. To see a detailed description of all dataset records, visit the JCU Research Data Catalogue.

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Email
Phone
Location
  • A1.230B, Chancellery Building (Cairns campus)
Advisory Accreditation
Primary Advisor
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