Time: 3:00 - 4:30pm Speaker: Dr. Mirco Musolesi, University College London and The Alan Turing InstituteVenue: PP1 People's Palace, Mile End Campus, Queen Mary University of London
The third colloquium of the Institute for Applied Data Sciences features as its guest presenter Mirco Musolesi, Reader in Data Science at UCL and Turing Fellow at the Alan Turing Institute - the event is open to everyone.Abstract: In the recent years, the emergence and widespread adoption of new technologies from social media to smartphones are rapidly changing the social sciences, since they allow researchers to analyse, study and model human behaviour at a scale and at a granularity that were unthinkable just a few years ago. These developments can be seen as the emergence of a new data-driven and computational approach to social science research, usually referred to as "computational social science”.In this talk I will discuss the work of my lab in a key area of this emerging discipline, namely the analysis and modelling of human behavioural patterns from mobile and sensor data. I will also give an overview of our work on mobile sensing for human behaviour modelling and prediction. I will present our ongoing projects in the area of mobile systems for mental health. In particular, I will show how mobile phones can be used to collect and analyse mobility patterns of individuals in order to quantitatively understand how mental health problems affect their daily routines and behaviour and how potential changes can be automatically detected. More in general, I will discuss our research directions in the area of anticipatory mobile computing, outlining open questions and opportunities for cross-disciplinary collaboration.Biography: Mirco Musolesi is a Reader in Data Science at University College London and a Turing Fellow at the Alan Turing Institute, the UK national institute for data science. At UCL he leads the Intelligent Social Systems Lab. He held research and teaching positions at Dartmouth, Cambridge, St Andrews and Birmingham. He is a computer scientist with a strong interest in sensing, modelling, understanding and predicting human behaviour and social dynamics in space and time, at different scales, using the "digital traces" we generate daily in our online and offline lives. He is interested in developing mathematical and computational models as well as implementing real-world systems based on them. This work has applications in a variety of domains, such as intelligent systems design, ubiquitous computing, digital health, security & privacy, and data science for social good. More details about his research profile can be found at: http://www.ucl.ac.uk/~ucfamus/
Contact: Dr Silvia LiveraniTel: +44 (0)20 7882 3370