I obtained my PhD in 2002 from the School of Electrical Engineering and ComputerScience, University of Newcastle, in Australia. After a year as a postdoctoral research fellow at the Business and Technology Laboratory in the University of Newcastle, Australia, I joined the School of IT at James Cook University, Australia. I have been actively involved in working on broad areas of geoinformatics and intelligence informatics. My research interests include geospatial data mining, multiple classifiers, geospatial databases, conceptual spaces, Web 2.0, map segmentation, clustering, geo-visualisation, internet of things, and Voronoi tessellations. Currently, I am working for intelligence and health informatics for the Tropics.

  • CP2408: Design Thinking and Creative IT Industries (Level 2; CNS & TSV)
  • CP2409: Network Forensics and Data Communications (Level 2; TSV)
  • CP3000: Research Topics in Technology (Level 3; CNS)
  • CP3403: Data Mining (Level 3; CNS & TSV)
  • CP5030: Special Topics 1 (Level 5; CNS)
  • CP5045: Information Technology Project (Level 5; CNS)
  • CP5080: Literature Review and Research Proposal (Level 5; TSV)
  • CP5634: Data Mining (Level 5; CNS & TSV)
  • Market analysis through online map segmentation
  • Geospatial data mining through clustering, association rules mining, and sequential mining
  • Trajectory mining for travel patterns and animal movements
  • Geocomputation, geo-engineering, geomatics and spatial data handling
  • Mobile augmented reality for learning and teaching
  • Voronoi tessellation and Delaunay triangulation applications
  • Applied artificial intelligence and machine learning algorithms
  • Data structure, computational geometry, data handling and management
  • 2010 to 2013 - Associate Professor, James Cook University (Cairns)
  • 2006 to 2009 - Senior Lecturer, James Cook University (Towsville)
  • 2003 to 2005 - Lecturer, James Cook University (Townsville)
  • 2002 to 2003 - Post-doctoral research fellow, The University of Newcastle (Newcastle)
Research Disciplines
  • 2012 - Best paper award in the 46th Hawaii International Conference on System Science
  • 2009 - Faculty Citation for Outstanding Contributions to Student Learning
  • 2007 - Best paper award in the Pacific Asia Workshop on Intelligence and Security Informatics
  • 2006 - Faculty Citation for Outstanding Contributions to Student Learning
  • 2004 - ACM (lifetime)

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 137+ research outputs authored by Prof Ickjai Lee from 2000 onwards.

Current Funding

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

Tropical Australian Academic Health Centre Limited - Research Seed Grants

Immersive virtual reality in a northern Queensland haemodialysis unit: A cross-over randomised controlled feasibility trial.

Indicative Funding
$18,000 over 2 years (administered by THHS)
This study will explore the feasibility and acceptability of an immersive VR experience for patients attending a north Queensland haemodialysis service and provide information to inform a multi-centre randomised controlled trial. Over the 4 week intervention period, participants will be offered a headset with vision of the local natural environment and with audio. Outcomes will be measured by participants: acceptability and usability of VR; attendance at scheduled dialysis sessions and adherence to lifestyle modifications; wellbeing, anxiety and depression; adverse events such as nausea. The feasibility and acceptability of the equipment from the clinicians? perspectives will also be explored.
Wendy Smyth, Cate Nagle, Joleen McArdle, John Body-Dempsey, Valli Manickam, Anne Swinbourne, Ickjai Lee and Jason Holdsworth (Townsville Hospital and Health Services, College of Healthcare Sciences and College of Science & Engineering)
Virtual reality; Haemodialysis; Distraction Therapy

Department of Industry - Innovations Connections

Develop an autonomous AI vehicle damage assessment tool (Phase II)

Indicative Funding
$49,894 over 1 year, in partnership with Hello Claims Pty Ltd ($49,895)
Improvement upon the project 1 developed method for automated detection, identification and categorisation of vehicle panel damage by developing a user interface and video vision. Semantic segmentation and deep learning networks will be further refined and developed for the next evolution/iteration of the software platform.
Ickjai Lee, Komal Khan, Kurt Schoenhoff and Thomas Napier (College of Science & Engineering)
Image classification; Deep learning; Data recognition; Semantic segmentation

Fisheries Research & Development Corporation - Annual Competitive Round

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

Indicative Funding
$115,649 over 2 years
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.
Jan Strugnell, Marcus Sheaves, Carlo Mattone, Ickjai Lee, Joanne Lee, Jason Holdsworth and Art (Hemmaphan) Suwanwiwat (College of Science & Engineering)
Abalone (Haliotidae); Machine Learning

World Wide Fund for Nature (US) - 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 1 year
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

Department of Industry - Innovation Connections - Entrepreneurs' Programme

Develop an autonomous AI vehicle damage assessment tool

Indicative Funding
$50,000 over 1 year, in partnership with Hello Claims Pty Ltd ($50,211)
Development of a practical means and method for automated detection, identification and categorisation of vehicle panel damage using AI, deep learning and selected semantic segmentation networks. Semi-Supervised methods will be investigated to minimize the requirements on hand made training data (archived damaged vehicle images) and research will be conducted to determine the possibility to build a minimum viable product (MVP) directly onto the existing platform architecture.
Ickjai Lee and Aidan Possemiers in collaboration with Kurt Schoenhoff (College of Science & Engineering)
Data recognition; Image Classification; Semantic segmentation; Deep Learning

Tree-Kangaroo and Mammal Group Inc - Contract Research

Kimberley - Wet Tropics Wildlife on Virtual Reality

Indicative Funding
This project will further develop 'Kimberley' the 3D virtual reality tree-kangaroo to the stage where the 'experience' can go live to the public at the Malanda Falls Visitor Centre. This project further extends 3D tree-Kangaroo with Virtual Reality and artificial intelligence.
Ickjai Lee, Aidan Possemiers and Peter Valentine in collaboration with David Hudson (College of Science & Engineering and Tree-Kangaroo and Mammal Group Inc)
Tree Kangaroo; Virtual Reality; Conservation; Simulation; Environment; Technology

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.

  • Exploring the Effects of Synchronous, Asynchronous and Blended Learning Approaches on Academic Learning Behaviours for Visual, Auditory and Kinaesthetic Learners (PhD , Secondary Advisor/AM)
  • Defending Deep Neural Network Systems from Malicious Data Poisoning Attacks (PhD , Advisor Mentor)
  • Investigation of Unconditionally Secure Multi-Party Protocols (PhD , Advisor Mentor)
  • Adaptive Technology Integration for Southeast Asia Secondary Schools (PhD , Advisor Mentor)
  • An Autonomous Tool to Produce Prototype Neural Networks for Deep Learning (PhD , Primary Advisor/AM/Adv)
  • An Automated approach to predict Sepsis in Adults from Electronic Medical Record (EMR) Data using Machine Learning and Natural Language Processing (PhD , Primary Advisor/AM/Adv)
  • Efficient Semantic Segmentation using Deep Learning. (PhD , Primary Advisor/AM/Adv)
  • Automatic Generation of Geometry for Simulation and Games (PhD , Primary Advisor/AM/Adv)
  • Contact mining from spatio-temporal trajectories (PhD , Primary Advisor/AM/Adv)
  • Machine Learning Algorithms for Time-Series and their Application to Restoration, Prediction and Quality Control of Oceanographic Data (PhD , Secondary Advisor)
  • User-intention based intrusion detection system for smart home (PhD , Secondary Advisor/AM)
  • Mobile Application for Fish Type Recognition (PhD , Secondary Advisor/AM)
  • No-bodies are still somebodies: Identifying characteristics of long-term missing persons within Australia (Masters , Secondary Advisor)
  • Fast Remote Diagnosis of Bowel Activities (PhD , Secondary Advisor/AM)
  • Developing novel methods that use AI algorithms for detecting and preventing information and cybersecurity threats (PhD , Secondary Advisor/AM)
  • HCI mobile eduation: Integrating learning, fun and turning addiction into performance (PhD , Secondary Advisor/AM)

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


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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