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SUMMARY:CNN seminar - Understanding and Exploiting Social and Mobility Inf
 ormation from Big Mobile Data - Dr Mirco Musolesi (University of Birmingha
 m)
DTSTART:20140121T163000Z
DTEND:20140121T173000Z
UID:TALK50315@talks.cam.ac.uk
CONTACT:Petra Vertes
DESCRIPTION:Abstract: Mobile phones are increasingly equipped with sensors
 \, such as accelerometers\, GPS receivers\, and cameras\, which can be use
 d to sense and interpret people behaviour in real-time. Novel user-centere
 d sensing applications can be built by exploiting the availability of thes
 e technologies. Moreover\, data extracted from the sensors can also be use
 d to model and predict people behaviour and movement patterns\, providing 
 a very rich set of multi-dimensional and linked data\, which can be extrem
 ely useful\, for instance\, for the development of highly personalised app
 lications\, health interventions\, and real-time support for policy-makers
 . \n\nIn this talk I will discuss some of our recent projects in the area 
 of large-scale scale data mining and modelling of mobile datasets with app
 lications to human mobility prediction and epidemic spreading containment.
   Indeed\, the study of the interdependence of human movement and social t
 ies of individuals is one of the most interesting research areas in comput
 ational social science. I will show how mobile phone data can be used to i
 mprove mobility prediction\, by characterising  and exploiting the correla
 tion between movements of friends and acquaintances. This can be seen as a
  process of discovering correlation patterns in networks of linked social 
 and geographic data. I will also discuss how data from mobile operators ca
 n be effectively exploited to model epidemic spreading and devise effectiv
 e containment strategies.\n\n\nBio: Dr. Mirco Musolesi is a Senior Lecture
 r at the School of Computer Science at the University of Birmingham. He re
 ceived a PhD in Computer Science from University College London in 2007. B
 efore joining Birmingham\, he held research positions at Dartmouth College
  and Cambridge and a Lectureship at the University of St Andrews. His rese
 arch interests lie at the interface of different areas\, namely ubiquitous
  computing\, large-scale data mining\, and network science. More informati
 on about his research profile can be found at the following URL: http://ww
 w.cs.bham.ac.uk/~musolesm
LOCATION:Keynes Hall in Kings College
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