The intention is to understand in which contexts you feel motivated to report about your personal state. A typical GT student has a very busy life and it becomes challenging for researchers to obtain self-reported information from them in a natural setting. Using the sensors on your phone it is possible to learn the best time to interrupt students for information. Predicting moments when participants of in-the-wild studies feel motivated to report data can potentially improve the quality of such data.
We are interested in ubiquitous computing and the research issues involved in building and evaluating ubicomp applications and services that impact our lives. Much of our work is situated in settings of everyday activity, such as the classroom, the office and the home. Our research focuses on several topics including, automated capture and access to live experiences, context-aware computing, applications and services in the home, natural interaction, software architecture, technology policy, security and privacy issues, and technology for individuals with special needs.
