JCU > Research Portfolio > Prof Ickjai Lee

About

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.

Teaching

CP3000: Research Topics in Technology (Level 3; CNS & TSV)
CP3413: Information Processing and Visualisation (Level 3; CNS & TSV)
CP5030: Special Topics 1 (Level 5; CNS & TSV)
CP5035: Special Topics 2 (Level 5; CNS & TSV)
CP5045: Information Technology Project (Level 5; CNS)
CP5080: Literature Review and Research Proposal (Level 5; CNS & TSV)
CP5120: Topics in Artificial Intelligence (Level 5; CNS & TSV)
CP5140: Topics in Media (Level 5; CNS & TSV)
CP5160: Topics in Software Development (Level 5; CNS & TSV)
CP5170: Topics in Systems and Networks (Level 5; CNS & TSV)
CP5330: Special Interest Topic 1 (Level 5; CNS & TSV)
CP5340: Special Interest Topic 2 (Level 5; CNS & TSV)

Interests

Research

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

Teaching

Data structure, computational geometry, data handling and management

Experience

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

Socio-Economic Objectives

Honours

Awards

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

Memberships

2004 - ACM (lifetime)
2004 - ACM-SIGSPATIAL

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

Munksgaard N, Lee I, Napier T, Zwart C, Cernusak L and Bird M (in press) One year of spectroscopic high-frequency measurements of atmospheric CO2, CH4, H2O and ?13C-CO2 at an Australian Savanna site. Geoscience Data Journal,
Napier T and Lee I (2023) Using mobile-based augmented reality and object detection for real-time Abalone growth monitoring. Computers and Electronics in Agriculture, 207.
Sinclair J, Suwanwiwat H and Lee I (2023) A hybrid data gathering and agent based cognitive architecture for realistic crowd simulations. Journal of Simulation, 17 (2). pp. 121-148
Li X, Ghodosi H, Chen C, Sankupellay M and Lee I (2022) Improving Network-Based Anomaly Detection in Smart Home Environment. Sensors, 22 (15).
Sinclair J, Suwanwiwat H and Lee I (2022) A Virtual Reality and Questionnaire Approach to Gathering Real World Data for Agent Based Crowd Simulation Models. Presence: Virtual and Augmented Reality, 28. pp. 293-312
Hussain E, Hasan M, Rahman M, Lee I, Tamanna T and Parvez M (2021) CoroDet: a deep learning based classification for COVID-19 detection using chest X-ray images. Chaos Solitons and Fractals, 142.
Liu S and Lee I (2021) Sequence encoding incorporated CNN model for Email document sentiment classification. Applied Soft Computing, 102.
Possemiers A and Lee I (2021) Evaluating deep learned voice compression for use in video games. Expert Systems with Applications, 181.
Bermingham L and Lee I (2020) Mining distinct and contiguous sequential patterns from large vehicle trajectories. Knowledge Based Systems, 189.
Liu H and Lee I (2020) Towards realistic meteorological predictive learning using conditional GAN. IEEE Access, 8. pp. 93179-93186

Conference Papers

Zhang B, Li J, Chen C, Lee K and Lee I (2022) A Practical Botnet Traffic Detection System using GNN. Lecture Notes in Computer Science. In: CSS 2021: Cyberspace Safety and Security, 9-11 November 2021, Virtual
Liu H and Lee I (2020) Bridging the gap between training and inference for spatio-temporal forecasting. Frontiers in Artificial Intelligence and Applications. In: ECAI 2020: 24th European Conference on Artificial Intelligence, 29 August - 8 September 2020, Santiago, Spain

More: ResearchOnline@JCU stores 143+ 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.

Department of Industry - Innovations Connections

ResPax Digital Passbook (Phase II)

Indicative Funding: $98,304 over 1 year
Summary: To continue the Phase I of project to further develop digital tools for collecting tourism data in the region to enable better decisionmaking.
Investigators: Ickjai Lee, Jason Holdsworth, Kurt Schoenhoff, Thomas Napier and Jarod Hine (College of Science & Engineering)
Keywords: Data mining; Data integration; Artificial intelligence; Information systems

Department of Industry - Innovations Connections

Develop the ResPax (digital) Passbook

Indicative Funding: $102,429 over 1 year
Summary: To develop digital tools for collecting tourism data in the region to enable better decision-making through various data mining approaches.
Investigators: Ickjai Lee, Jason Holdsworth, Kurt Schoenhoff, Thomas Napier and Jarod Hine (College of Science & Engineering)
Keywords: Data Mining; Data Integration; Artificial Intelligence; Information Systems

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 Townsville Hospital and Health Service)
Summary: 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.
Investigators: Wendy Smyth, Cate Nagle, Joleen McArdle, John Body-Dempsey, Valli Manickam, Anne Swinbourne, Ickjai Lee and Jason Holdsworth (Townsville Hospital and Health Service, College of Healthcare Sciences and College of Science & Engineering)
Keywords: Virtual reality; Haemodialysis; Distraction Therapy

The World Wide Fund for Nature, Australia - Contract Research

JCU Spawning Potential app development

Indicative Funding: $37,500 (administered by World Wide Fund for Nature Australia)
Summary: The central biological measure of success for the ?Community- Based Sustainable Development in Solomon Island and PNG Coastal Communities? projects are trends in the Spawning Potential Ratio (SPR) of key target species. This Project seeks to refine the Spawning Potential Survey (SPS) App (JCU FISH) to include spatial reporting tools that can be utilised by survey participants to monitor spatial and temporal trends in SPR. This project extends from an earlier ?proof of concept? project funded by the WWF Ocean Practice where the potential for automatic identification and measurement of target species from a single image was realised.
Investigators: Marcus Sheaves, Ickjai Lee, Jason Holdsworth and Michael Bradley (College of Science & Engineering)
Keywords: Reef Fish; Pacific Islands; Fisheries; App; Catch data; Monitoring

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)
Summary: 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.
Investigators: Ickjai Lee, Komal Khan, Kurt Schoenhoff and Thomas Napier (College of Science & Engineering)
Keywords: 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
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 (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
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

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)
Summary: 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.
Investigators: Ickjai Lee and Aidan Possemiers in collaboration with Kurt Schoenhoff (College of Science & Engineering)
Keywords: Data recognition; Image Classification; Semantic segmentation; Deep Learning

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

Deep Learning Augmented Anomaly Detection for Flight Data (PhD , Secondary Advisor/AM)
Fast Remote Diagnosis of Bowel Activities (PhD , Secondary Advisor/AM)
Sustaining Chinese Mazu Cultural Heritage in Tourism through VR Technology: Insights from East and Southeast Asia (PhD , Advisor Mentor)
A Study of Human Resource Training and Front-Line Service Quality through Gamification in the Hospitality Industry: Comparisons from the Hotel Sector in Singapore, Kuala Lumpur and Colombo (PhD , Advisor Mentor)
Efficient Semantic Segmentation using Deep Learning. (PhD , Primary Advisor/AM/Adv)
Autonomous CNN architecture selection and dynamic modification through proven convolutional architectures and transfer learning. (PhD , Primary Advisor/AM/Adv)
Contact mining from spatio-temporal trajectories (PhD , Primary Advisor/AM/Adv)
Species Classification using deep learning-Based signal processing techniques in natural soundscapes (PhD , Primary Advisor/AM/Adv)
Lightweight Self-supervised learning for Image Classification and Object Recognition (PhD , Secondary Advisor/AM)
HCI mobile eduation: Integrating learning, fun and turning addiction into performance (PhD , Secondary Advisor/AM)
Representing user behaviour profile in space for robust, non-invasive, adaptive, high performing, efficient, and continuous user authentication (PhD , Secondary Advisor/AM)

Completed

Document-level sentiment analysis of email data (2020, PhD , Primary Advisor/AM/Adv)
A data-driven approach towards a realistic and generic crowd simulation framework (2020, PhD , Primary Advisor/AM/Adv)
No bodies are still somebodies: Evaluating the use of public online information to develop a dataset of characteristics on long-term missing persons within Australia (2023, Masters , Secondary Advisor)
Investigation of unconditionally secure multi-party computation (2023, PhD , Advisor Mentor)
Culture-Centred Integration of ICT in Southeast Asia Secondary Schools (2023, PhD , Advisor Mentor)
Periodic pattern mining from spatio-temporal trajectory data (2018, PhD , Primary Advisor/AM/Adv)
Predictive spatio-temporal modelling with neural networks (2020, PhD , Primary Advisor/AM/Adv)
From spatio-temporal trajectories to succinct and semantically meaningful patterns (2018, PhD , Primary Advisor)

Data

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

Myers, T. (2014) ICT student's interpersonal soft skills in online teaching environments using traditional active learning techniques. James Cook University

Collaboration

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.