Congratulations Meng-Wei (Daniel) Chang!

Descriptive NPR Lens Widget

Meng-Wei (Daniel) Chang has become the lab’s first graduate!  Daniel completed his M.Sc. thesis defense successfully on Thursday November 22.  His research investigated ways to visualize text through varying rendering techniques on 3D objects.  His SurfNet-funded work touches on text processing, information visualization, scientific visualization, and multitouch application design.  He created a very polished prototype application for exploring a collection of 600,000 car incident reports.  Car part words are extracted from the reports and their occurrence counts are visualized on a 3D model of a car, so that parts which are mentioned more often in failure reports stand out in the 3D view.  Interactive widgets support exploration of the data across time, across various car models, and co-occurrence relationships between parts.  This visualization technique could be used to visualize product reviews, hotel reviews, or any sort of text which mentions parts of a scene or of an object which can be rendered using non-photorealistic techniques.