Projects

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Undistracted Driving and Mobile Messaging, PI

In United States alone, operating mobile phones while driving has been cited as a factor in crashes that have led to 995 deaths and 24,000 injuries in 2009. Our approach to undistracted driving answers many mobile information needs drivers have without drivers having to operate the mobile phone at all. We implement novel approaches such as time-shifting, burden-shifting and activity-based sharing by using context-awareness provided by modern mobile phone platform sensors. This project has led to a paper appearing in Hotmobile'11 and a poster in AutomotiveUI'10.

Understanding Social-Driven Mobile Sharing

We have studied motivations, uses and gratifications of people using foursquare, a service that allows users to share their location by checking-in to places. We have discovered novel insights of privacy management and self-representation in mobile social networks. This project has led to a paper appearing in CHI'11, the premier international conference of human-computer interaction.

End-User Programming for Context-Aware Mobile Mashups

The key motivation for the project is that although there are point solutions for creating e.g. location-based reminders for specific tasks (such as "Remember the Milk"), there is no platform for casual users to create reminders where the context can be time, location or information on the Internet.

Privacy for Mobile Internet, PI

A current thrust of this project is Caché - a framework for providing location privacy for users of location-based services. The key insight behind Caché is to use the bandwidth and storage capabilities of modern mobile systems as a tradeoff for hiding the users' real location.

Android Application Scanner, co-PI

We aim to provide user-friendly ways for end-users to decide whether they should install an application from a mobile phone application market. Today's mobile phones provide users with very coarse-grained information about application's permissions and capabilities, we want to empower users to make better decisions. The project is funded by US Army Research Labs through CMU CyLab.