Associate Professor Paul Kwan
PhD GradCertHighEd MSc BScAssociate Professor - ICT-702955
School of Engineering and Technology
Centre for Intelligent Systems
Associate Professor Paul Kwan has significant experience in Computer Science, Information and Communication Technology (ICT) and Data Science education and research for over 20 years. He is currently Associate Professor - ICT in the School of Engineering and Technology (SET) at CQUniversity Australia (Brisbane Campus). Before joining CQUniversity, he was Professor in Data Analytics at Melbourne Institute of Technology (2000-2023), where he led the Data Analytics program and coordinated Master of Data Analytics, Graduate Certificate in Data Analytics, and Master of Business Analytics. From 2004 to 2019, he was with the School of Science and Technology at University of New England (UNE) in Armidale, NSW, where he was Professor and Discipline Head of Computer Science between 2014 and 2019.
Associate Professor Kwan's primary research fields are Artificial Intelligence and Data Science. Within these fields, his expertise include Computer Vision, Data Mining, Machine Learning, and Computational Modelling. His expertise has informed applied research in image retrieval, biometrics authentication, dimensionality reduction, agent-based modelling, digital agriculture, and learning analytics. To date, he has published over 120 peer-reviewed papers and refereed articles in international conferences and journals in Artificial Intelligence, Computer Vision, Data Science, Machine Learning, Pattern Recognition, Digital Agriculture, and Learning & Teaching Analytics.
In addition, Associate Professor Kwan has successfully received competitive research grants from external organizations including Australian Research Council Discovery Project (ARC DP), Australia-China Science and Research Fund, Department of Agriculture, Animal Health Australia, Australian Sheep CRC, Australian Academy of Technology and Engineering, Australian Office for Learning and Teaching, Hort Innovation Australia, and Queensland Government Department of the Environment, Tourism, Science and Innovation (DETSI).
Background
Associate Professor Kwan has significant experience developing and managing Computer Science, Information and Communication Technology, Data Analytics, and Business Analytics courses at both undergraduate and postgraduate levels. His high quality of teaching has been recognised through multiple teaching commendations and awards received over his academic career.
In addition, Associate Professor Kwan has an outstanding record of successful Higher Degree Research and Honours students’ supervision. Until now, he has supervised 15 PhDs (10 principally), 3 Research Masters, and 4 Honours students (three were University Medalists) to completion. In 2014 and 2015, he was designated a Vice Chancellor's Scholar Nominated Academic for excellent contributions in mentoring high achieving Computer Science students at UNE. Currently, he is supervising 2 PhD and 3 Master of Research students at CQUniversity.
Universities Studied At
Curtin University (Australia)
- Graduate Certificate in Higher Education Innovative Learning and Teaching (October 2022)
University of Tsukuba (Japan)
- PhD, Advanced Engineering Systems (March 2003)
University of Arizona (USA)
- MSc, Computer Science (December 1988)
Cornell University (USA)
- BSc, Computer Science (June 1986)
Universities Worked At
Associate Professor Kwan started his academic career in Australia at The University of New England (UNE) in Armidale, NSW. Appointed a Lecturer in Computer Science in 2004, he was promoted to Professor in January 2017. Between 2014 and 2019, he was the Discipline Leader of Computer Science in the School of Science and Technology. In that role, Associate Professor Kwan led the teaching and learning initiatives, research, and administration activities for the discipline which comprised 10 academic staff.
Between January 2020 to November 2023, he was Professor and Program Leader in Data Analytics at Melbourne Institute of Technology (MIT), where he provided leadership and course coordination for the Master of Data Analytics, Graduate Certificate in Data Analytics, and Master of Business Analytics. Until now, Associate Professor Kwan has significant experience in leading an academic discipline at both a public university and a non-university higher education provider in his academic career.
Awards
Associate Professor Kwan's PhD study was fully funded by the Monbukagakusho Scholarship (1999-2003), which is a prestigious academic scholarship awarded by the Japanese Ministry of Education, Culture, Sports, Science and Technology.
He was the recipient of multiple teaching commendations for various Computer Science and Information Technology subjects he coordinated and taught at UNE. These commendations were awarded for high overall student satisfaction, exemplary teaching practices, and low attrition in teaching. Furthermore, he was recognised externally by THEunijobs as Lecturer of the Year (Top 10 Nominations) at UNE in 2009.
In 2014 and 2015, Associate Professor Kwan was designated by the Vice Chancellor at UNE as a VC Scholar Nominated Academic for his significant contributions in mentoring high achieving Bachelor of Computer Science students.
In 2025, as a member of the ConnectedAI team, Associate Professor Kwan and two School of Engineering and Technology colleagues (Dr. Mohammad Saiedur Rahaman and Dr. Ahsan Morshed) received the Vice-Chancellor's Award for Best Practice in Learning and Teaching (in the Best Emerging Practice in Generative AI category).
Previous teaching
Computer Science/Information Technology
- Introduction to UNIX and Professional Practices
- Object-Oriented Programming
- Data Structures and Algorithms
- Artificial Intelligence
- Data Mining
- Knowledge Management Systems
- Operating Systems
- Computer Networks
- ICT Practices
- Advanced Web Programming
- Internet Publishing
- Project Management and Research Methods
Data Analytics
- Mathematical and Statistical Methods
- Data Science
- Business Data Analysis
- Predictive Analytics
- Research Project for Analytic Professionals
- Data Analytics Capstone Project
- Business Analytics Capstone Project
Professional Experience
In terms of services to his discipline, Associate Professor Kwan is currently a Senior Member of Association of Computing Machinery (ACM), a Senior Member of IEEE, and a Professional Member of Australian Computer Society (ACS). He has actively contributed to the broader research community through serving as Associate Editor for International Journal of Wavelets, Multiresolution and Information Processing (World Scientific, ISSN 0219-6913), Editor for Research in Mathematics (Taylor & Francis Online, ISSN: 2768-4830), Section Editor of 'Precision and Digital Agriculture' for MDPI Agronomy (ISSN: 2073-4395), Guest Editor for MDPI Sensors (ISSN: 1424-8220), and Expert Assessor for ARC National Competitive Grant Schemes.
Associate Professor Kwan has also actively involved in promoting advances in AI applications in Precision and Digital Agriculture through organising focused special issues in relevant refereed journals. In 2021, he organised the Special Issue on “Data-Driven Agricultural Innovations” for the Agronomy Journal which attracted a series of high-quality contributions. Similarly, he was the principal guest editor for another two Special Issues, one on “Data-Driven Agricultural Innovations with Artificial Intelligence and Industrial Internet of Things (IIoT)” for the Agriculture Journal and another on “Advances in Agriculture Sensor Technologies and Their Applications in Precision Agriculture and Smart Farming” for the Sensors Journal. Currently, he is the principal guest editor for the open Special Issue on "Intelligent Sensors and AI for Sustainable Agriculture and Ecological Solutions" for the Sensors Journal.
Professional Memberships
Member, Australian Computer Society (2006 - Present)
Senior Member, Association for Computing Machinery (2008 - Present)
Senior Member, Institute of Electrical and Electronics Engineers (2010 - Present)
Responsibilities
Associate Professor Kwan is currently Acting Postgraduate Research Coordinator for the School of Engineering and Technology (SET) at CQUniversity.
Professional Interests
I am interested in establishing interdisciplinary research collaborations with stakeholders from government and industries.
Editor
Associate Editor: International Journal of Wavelets, Multiresolution and Information Processing (World Scientific, ISSN: 0219-6913)
Editor: Research in Mathematics (Taylor & Francis Online, ISSN: 2768-4830)
Section Editor: “Precision and Digital Agriculture”: Agronomy Journal (MDPI, ISSN: 2073-4395)
Advancing AI-Driven Vegetation Segmentation for Precision Agriculture (RUIC006)
Grant: Competitive Grant (Category 2: Other Public Sector)
Funding Schemes: Queensland Government Department of the Environment, Tourism, Science and Innovation (DETSI) Regional University Industry Collaboration (RUIC) Program 2024-2027 THROUGH CSIRO; InFarm Pty Ltd - Regional University Industry Collaboration (RUIC) Program 2024-2027 - Project RUIC006
Total Funding: $100,000.00
Optimising capsicum and chilli quality (VG24002)
Grant: Competitive Grant (Category 3: Industry and Other)
Funding Schemes: Hort Innovation VG24002 Optimising Capsicum and Chilli Quality
Total Funding: $1,686,642.52
Accreditation
I am currently accredited for supervision in the following:
- 4102 Ecological Applications
- 4609 Information Systems
- 3903 Education Systems
- 4601 Applied computing
- 4602 Artificial intelligence
- 4603 Computer vision and multimedia computation
- 4605 Data management and data science
- 4608 Human-centred computing
- 4611 Machine learning
- 4612 Software engineering
Current Capacity
Current Supervision
Specialist Studies in Education - Learning analytics
Applied computing - Applications in social sciences and education
Artificial intelligence - Autonomous agents and multiagent systems
Computer vision and multimedia computation - Image and video coding
Computer vision and multimedia computation - Pattern recognition
Data management and data science - Data engineering and data science
Machine learning - Deep learning
Statistics - Statistical data science
