Who Am I ? Jingtao Wang, Assistant Professor in CS and LRDC (jingtaow@pitt.edu , will become jingtaow@cs.pitt.edu eventually) Office 5423 SENSQ http://www.cs.pitt.edu/~jingtaow.

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Presentation transcript:

Who Am I ? Jingtao Wang, Assistant Professor in CS and LRDC (jingtaow@pitt.edu , will become jingtaow@cs.pitt.edu eventually) Office 5423 SENSQ http://www.cs.pitt.edu/~jingtaow Ph.D. in Computer Science from UC Berkeley Originally from China, worked as a researcher at IBM China Research Lab for three years after getting M.S. and B.S. degrees from Xi’an Jiaotong University Primary research direction - Human Computer Interaction (HCI) Mobile interfaces, the application of machine learning in HCI and education/learning

Past Projects

Embodied Visual Exploration of Multidimensional Scatterplots on Mobile Devices Scatterplots is one of the most widely-used visual representations for multidimensional data Even if we employ 3D graphics, point color, shape, and size as graphical properties, a standard scatterplot diagram can only visually represent a handful of data dimensions at a time. It becomes more challenging on mobile devices with the limitation of screen size, screen resolution and input devices Source: www.moleculardevices.com www.japanreview.net disc.sci.gsfc.nasa.gov

Project Outline Using a Scatterplot Matrix [Elmqvist 2008] to present a global overview of the different dimensions and historical navigations of the data set Using embodied interaction techniques (Yaw, pitch, and roll rotations, pinch/zoom) to navigate the scatterplot matrix interactively [Elmqvist 2008]

Designing A New Phrase Set for Evaluating Mobile Text Entry Techniques in the “Twitter Age” Text entry on mobile devices present unique challenges to the fields of human computer interaction Many mobile text entry methods have been invented in the past 15 years. To verify the efficacy of a new technique, one has to run a typical A vs. B style benchmark on a set of test phrases The most popular mobile phrase set – [MacKenzie 2003], were designed to emulate the character/word/di-graph properties of English novels. It’s becoming less representative/relevant in the “Twitter Age”