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Invited Speaker


Title: Reality Mining for Real: Large-Scale Human Behavior and Smartphone Data

The large-scale understanding of personal and social behavior from smartphone sensor data is an emerging trend in computing. Smartphones can constantly sense human location, motion, proximity, and communication, and represent one of the most accurate means of tracing human activities. All this data,as never before, is being generated at massive scales.

I will present an overview of recent work in my research group in this domain, which is addressing mobile sensing, data analysis, and applications. I will first describe our experience with the collection of a rich corpus of real life data using smartphones as sensors, and discuss a few of the many associated challenges - both human and technological. I will then present computational methods that we have developed to discover a variety of patterns, including daily routines of individuals, trends of phone application usage, social interaction types, and personality traits. I will finally discuss about open issues in this domain.


Daniel Gatica-Perez is a senior researcher at Idiap Research Institute and the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, where he directs the Social Computing Group. His research integrates methods from multimedia signal processing, machine learning, ubiquitous computing, and social sciences to develop computational models for human and social behavior analysis from sensor data. His recent work has studied small groups at work in multisensor spaces, populations of smartphone users in urban environments, and on-line communities in social media. His work
has been supported by the Swiss and US governments, the European Union, and industry. Among several professional activities, he currently serves as Associate Editor of the IEEE Transactions on Multimedia, Image and Vision Computing, and the Journal of Ambient Intelligence and Smart Environments.