Dr. Joanne Lee received her PhD degree in Computer Science in 2007 from Griffith University, Australia. She started her academic career as a lecturer in School of Business and IT at Charles Sturt University, Australia (2007-2008) and continued her academic pursuit after moving to James Cook University.

Joanne is an active researcher, and her research interests include machine learning, algorithm optimisation, neural networks, data mining, and applied artificial intelligence. She has been involved in various projects developing a real-world scheduling optimisation system for fly-in-fly-out mining employee scheduling, designing and implementing a non-destructive neural network based classification system for ultrasonic signals, and developing spatio-temporal mining algorithms for moving objects.

Joanne’s teaching experience covers from introductory machine learning, database, data mining, 3D modelling, and programming. Currently, she is supervising 5 PhD students, and 3 of them are near completion.

  • CP1404: Programming II (Level 1; CNS)
  • CP2403: Information Processing and Visualisation (Level 2; CNS & TSV)
  • CP2404: Database Modelling (Level 2; CNS & TSV)
  • CP2405: Collective Intelligence and Entrepreneurship (Level 2; CNS & TSV)
  • CP3413: Information Processing and Visualisation (Level 3; CNS & TSV)
  • CP5635: Collective Intelligence and Entrepreneurship (Level 5; TSV)
  • 2007 to 2008 - Lecturer, Charles Stuart University (Albury-Wodonga)
Research Disciplines
Socio-Economic Objectives

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

ResearchOnline@JCU stores 52+ research outputs authored by Dr Joanne Lee from 2003 onwards.

Current Funding

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

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
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.
Marcus Sheaves, Carlo Mattone, Michael Bradley, Joanne Lee, Jason Holdsworth, Art (Hemmaphan) Suwanwiwat and Ickjai Lee (College of Science & Engineering)
Artificial Intelligence; Phone App; Caught Fish; Catch Rate

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.

  • An Autonomous Tool to Produce Prototype Neural Networks for Deep Learning (PhD , Secondary Advisor)
  • Efficient Semantic Segmentation using Deep Learning. (PhD , Secondary Advisor)
  • Document-level Sentiment Analysis of Email Data (PhD , Secondary Advisor)
  • Fast Remote Diagnosis of Bowel Activities (PhD , Secondary Advisor)
  • Mining Human Mobilty Relationship through Spatio- temporal Trajectories (PhD , Secondary Advisor)
  • Adaptive traffic surveillance system using machine learning for monitoring unlawful conducts on the road (PhD , Secondary Advisor)
  • Establishing an Empirical basis for the Curriculum and Assessment of the Competency based Fellowship of the Royal Australian and New Zealand College of Psychiatrists by Text Mining the Psychiatric Literature (PhD , Secondary Advisor)

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