BA NTU, MA NTHU, PhD Rutgers
My personal website is http://csusap.csu.edu.au/~yingliu
I am currently a Lecturer in Information Management at the School of Information Studies, Charles Sturt University (CSU). I am also a visiting fellow from the College of Engineering and Computer Science at the Australian National University since January 2012. I am a full member of Institute for Land, Water and Society at CSU since 2017.
I earned my Ph.D. in Information Science from School of Communication and Information, Rutgers University in the US in 2009. My primary research and teaching areas lie at the intersections of interactive information retrieval, organisation of information and human information behaviour, with an emphasis on user-centred information access system design and evaluation.
My primary research areas lie at the intersections of interactive information retrieval, organisation of information and human information behaviour, with an emphasis on user-centred information access system design and evaluation. This program of research is concerned with people's interactions with information retrieval systems, such as modern search engines. At a theoretical level, my research focuses on the theories of human concept formation and their implications for information access. At the applied level, I am interested in the design and evaluation of information retrieval systems. User experiments, eye tracker and usability techniques have been applied in my research projects.
Computational Intelligence for Complex Structured Data
2015-2018 (Chief Investigator)
$275,000, funded by the Australian Research Council (ARC), Linkage Projects scheme, LP140100995
Collaborators: Professor Tamás (Tom) Gedeon (ANU), Professor Andreas Nürnberger (University of Magdeburg, Germany), Professor Péter Baranyi (Hungarian Academy of Sciences) and Dr Richard Jones (ANU).
This project is to investigate adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens, such data could be networks of academic citations, or named entities in an investigation. Most current tools are operated using point/click/drag metaphors on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax & semantics of individual gestures and actions, nor the multi-gesture information fusion required for 'understanding'. All of this is done naturally by most human beings, using biological neural networks.
Understanding the Role of Social Media in Disaster Management: A Systematic Investigation of Mixed-Mode Individual Information Behaviours
$89,560 (SGD), funded by the Ministry of Education (MOE) Academic Research Funding (AcRF) Tier 1, 2015-T1-002-150
Collaborators: Dr Chih-Hui Lai (Nanyang Technological University), Collaborators: Dr Tang Tang (University of Akron), Dr Xuebin Wei (James Madison University) and Dr Bing She (University of Michigan).
This study tackles the problem of social media use in the disaster context by examining individuals' information and communicative behaviours, and delving into the social context of the behaviours during and beyond disaster times.
My general teaching areas are information retrieval, research methods, web design and information architecture.
My teaching philosophy is to encourage students to develop their critical thinking skills through the reflection of their learning processes and the engagement with class discussions. To achieve these objectives, I have encouraged students to formulate their own questions by reflecting on their understanding of course materials on discussion forums through various exercises and learning activities. In addition, I take the experiential learning approach to the learning and teaching of procedural knowledge, with particular reference to the use and application of information technologies.