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Mobile devices, such as cell phones, small tags and sensors, are becoming highly pervasive: they are remarkably inexpensive enabling a widespread deployment. The integration of large numbers of small computing and storage devices into pervasive computing environments offers a tremendous application potential that we have just begun to harness. These technologies create a rich environment for complex information management systems and will drive computing for the next decade. Their applications will transform the way we live, ranging from continuous access to location-based services from virtually anywhere at any time, to traffic systems optimizing the traffic flow using real-time data monitored by sensor-enabled cars.
In general, my research focuses on spatial algorithms for pervasive computing environments that anticipate, adapt, and respond to the needs of users. In my work I address a key research challenge: how to efficiently collect and process an abundance of heterogeneous, possibly imprecise data and how to transform it into useable information. The continuous collection of data with a high degree of spatial precision also holds privacy risks, and my research investigates privacy-aware algorithms that ensure high-quality location-based services without revealing the precise location or identity of a user accessing those services.