Epidemics (journal) This paper describes the collaborative efforts from the RAMPVIS consortium to help the epidemiologists modelling the various aspects of Covid19, including the spread of the disease and the impact of different isolation policies. Started as a voluntary effort, there are many challenges faced by the group of close to 20 visualisation experts, including […]
Data Scientist at Red Sift, 2011-2017, “Spatial-Temporal Analysis of Online Social Information and its Provenance using Visual Analytics”, School of Engineering and Information Sciences, Middlesex University, UK.
The workshop is organised by the Creative Industry Knowledge Transfer Network and was held at the Nesta in London. The workshop had some excellent speakers and I am quite honoured to be invited. Below are the presentation slides.
This is presented at the Visual Analytics Summer School 2013, and below are the slides
This is the second Dagstuhl Seminar I attended this year. Just as before, it is very interesting and intensive. Met several old friends and got to make a lot new friend. I am busy writing a book chapter on Multivariate Network Visualization now as the result.
Dagstuhl Seminar is an invitation only workshop that experts from all over the world to work on a specific topic intensively for a week in a remote research institute (an old castle) in Germany. This one is about curved edges in graph visualisation, which I just did a study last year.
The conference will be in Sydney, Australia next year and I really hope I can attend.
This is an entry to the Mini Challenge 1 of the VAST Challenge 2012. The details are here. Below is a video describing the solution.
This is an extended version of the work presented as a poster at Diagrams 2012 with new user study and analysis. Kai Xu, Chris Rooney, Peter Passmore, and Dong-Han Ham, “A User Study on Curved Edges in Graph Visualisation”, IEEE Information Visualization Conference, 14-29 October 2012, Seattle, US. PDF
“Graph Layout Methods and Their Visual Perception”, Visual Analytics Summer School, August 2012, London, UK
Human-Machine Learning 
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