Author Archives: dat

About dat

Dat Tran received his B.Sc. and M.Sc. degrees from University of Science, Vietnam, in 1984 and 1994, respectively. He moved to Australia with his family in August 1995. He received his Graduate Diploma in Information Sciences and Ph.D. degree in Information Sciences & Engineering from University of Canberra, Australia in 1996 and 2001, respectively. Currently, he is an Associate Professor in Software Engineering at Faculty of Information Sciences and Engineering, University of Canberra, Australia.

Machine Learning for Classification Problems

Projects

  • Support Vector Machine: Multi-hyperplane Approach
  • Support Vector Data Description: Multi-hypersphere Approach
  • Unified Model for Support Vector Machine and Support Vector Data Description
  • Artificial Immune Systems
  • Grammatical Dependency-Based Relations for Term Weighting in Text Classification
  • Metrics for Face Recognition Using Local Binary Patterns

Researchers

  • Wanli Ma (University of Canberra, Australia)
  • Trung Le (Deakin University, Australia)
  • Phuoc Nguyen (Deakin University, Australia)
  • Van Nguyen (HCMc University of Pedagogy, Vietnam)
  • Thai Hoang Le (HCMc University of Science, Vietnam)
  • Anh Le (HCMc University of Pedagogy, Vietnam)
  • Dat Tran (University of Canberra, Australia)
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CIKADA

CIKADA aims at developing an interdisciplinary research group for bringing together researchers pursuing research in computational intelligence and knowledge discovery to model and simulate real-world problems. CIKADAs focus includes fuzzy pattern recognition, artificial immune systems, evolutionary algorithms and systems, kernel methods, intelligent agents, multi-agent systems, and knowledge discovery research on neural

networks, support vector machines, genetic algorithms and hybrid models. CIKADA will investigate those models and apply them to discover useful knowledge from various forms of data in security, e-health, brain-computer interface, educational systems, financial forensics, biometric engineering, sport modelling, social modelling soft computing, smart technologies for green systems and smart commerce systems. Research in CIKADA focuses at producing workable solutions to complex real world problems.

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CIKADA

CIKADA aims at developing an interdisciplinary research group for bringing together researchers pursuing research in computational intelligence and knowledge discovery to model and simulate real-world problems.CIKADA aims at developing an interdisciplinary research group for bringing together researchers pursuing research in computational intelligence and knowledge discovery to model and simulate real-world problems

Comments Off on CIKADA

CIKADA

CIKADA aims at developing an interdisciplinary research group for bringing together researchers pursuing research in computational intelligence and knowledge discovery to model and simulate real-world problems. CIKADAs focus includes fuzzy pattern recognition, artificial immune systems, evolutionary algorithms and systems, kernel methods, intelligent agents, multi-agent systems, and knowledge discovery research on neural networks, support vector machines, genetic algorithms and hybrid models. CIKADA will investigate those models and apply them to discover useful knowledge from various forms of data in security, e-health, brain-computer interface, educational systems, financial forensics, biometric engineering, sport modelling, social modelling soft computing, smart technologies for green systems and smart commerce systems. Research in CIKADA focuses at producing workable solutions to complex real world problems.

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Dat Tran
BSc, MSc USVN, PhD Inf. Sci. UC
Associate Professor
Address: University of Canberra, Faculty of Education Science Technology and Mathematics, ACT 2601, Australia
Office: 6C72, Phone: +61 2 6201 2394 Fax: +61 2 6201 5231
Email: dat.tran@canberra.edu.au
Web: http://staff.estem-uc.edu.au/dtran/

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