Associate Professor Quang Vinh Nguyen

Computer Science (School of Computing, Engineering and Mathematics)
Research Program: Human-Machine Interaction

Biography

Dr Quang Vinh Nguyen is a Senior Lecturer in Visual Analytics whose main research areas are Visual Analytics and Information Visualization, including Medical Data Analysis, Graph and Network Analysis, Graph Drawing, Applications with Visualization and Visual Analytics, Visual Collaborative System, Human Computer Interaction, and related research areas.

His research is now focusing on theoretical and domain specific research on Visual Analytics and Information Visualisation based on the synergy of both human's visual strength and automated analysis, particularly for large scale-relational data and network, medical data analysis and related applications. He belongs to the Human-Machine Interaction research program at MARCS Institute.

Research Interests

• Relational Data Visualization
  In real world, hierarchical structures are often very large with thousands or even millions of elements and relationships. As a result, providing an interactive visualisation of the entire structure, with capability for deep exploration at different levels of granularity is crucial for the analysts in the knowledge discovery process. This project develops new techniques and algorithms for quickly partitioning and visualising very large hierarchical structures.
• Visual Analytics for medical data
  This project is to develop new technologies for the extraction of knowledge from both complex biomedical and genomic data and then visualise them in a meaningful and interpretable way. The development includes enabling algorithms and technologies through an approach that will synergise the powerful visual analytics, including automated data analysis and visualisations, and the expertise of domain experts in the medical field.
• Visual Analytics for multi-dimensional data
  Real-world data is usually very large and complex, scalability and high-dimensionality problems remain challenges for visual data analysis. Data is typically available is the tabular forms with several attributes or dimensions, such as database tables and spread sheets. Understanding of the vast information is almost impossible without an effective visualisation and analysis tools. This project investigates customisable visual analytics tools using multi-attributed scatter plots and state-of-the-art visualization methods for manipulating the multi-dimensional data.
• Intelligent Visual Analytics
  The goal of this project is to develop new methodologies and technologies for extraction of knowledge from huge relational data such as networks and graphs, using intelligent visual analytics and machine learning. This goal rests on the development of enabling algorithms and technologies through an approach that will synergise both human's visual strengths (including visual perception, sense making and pattern recognition) and machine learning (including rules and classification). Analysts can visually specifying new rules or hypotheses for interactive visualisations and knowledge discovery which can be shared amongst analysts for further refinement or usage.

Qualifications and Honours

Doctor of Philosophy in Computing Sciences, The University of Technology, Sydney
Master of Science in Computing, The University of Technology, Sydney
Bachelor of Computer Science and Technology, The University of Sydney

Roles

Senior Lecturer in Visual Analytics

Full Publications

For a full listing of my publications please see my personal publications page.(opens in a new window)

Contact Quang