Jul 2011

Mirco Musolesi, Sensing, Understanding and Modelling People using Mobile Phones


Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, that can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of such technologies in these devices that are part of our everyday experience. Moreover, data extracted from the sensors can also be used to model people behaviour and movement patterns providing a very rich set of multi-dimensional data, which can be extremely useful for social science, marketing and epidemiological studies.

In this talk I will present some of my recent work in this area including the design and implementation of the CenceMe platform, a system that supports the inference of activities and other presence information of individuals using off-the-shelf sensor-enabled phones and of EmotionSense, a system for supporting social psychology research. Finally, I will discuss the issues related to the design of energy-efficient social sensing systems.

About Mirco:

Dr. Mirco Musolesi is a SICSA Lecturer at the School of Computer Science at the University of St. Andrews. He received a PhD in Computer Science from University College London in 2007 and a Master in Electronic Engineering from the University of Bologna in 2002. From October 2005 to August 2007 he was a Research Fellow at the Department of Computer Science, University College London. Then, from September 2007 to August 2008 he was an ISTS Postdoctoral Research Fellow at Dartmouth College, NH, USA, and from September 2008 to October 2009 a Postdoctoral Research Associate at the Computer Laboratory, University of Cambridge. His research interests lie in the broad area of mobile systems and networking with a current focus on intelligent mobile systems, online social networks, application of complex network theory to networked systems design, mobility modelling and sensing systems based on mobile phones. More information about his research profile can be found at the following URL: