Networks are all around us. As such, network science is crucial for our understanding of many applications of high societal relevance (e.g., social and technological networks, epidemics, biological networks). Our research focuses on developing new machine learning methods to discover complex interactions and collective behaviors that determine how various types of events and behaviors in social networks are generated and propagated. In particular, we are interested in developing new approaches for social sensing that are relevant to the immediate concerns around pandemic detection and mitigation.
In: IEEE Journal on Selected Areas in Communications, vol. 32, no. 12, pp. 2344–2353, 2014.
In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 846–853, 2013.
In: IEEE Journal on Selected Areas in Communications, vol. 31, no. 12, pp. 879–890, 2013.
In: IEEE Journal on Selected Areas in Communications, vol. 31, no. 12, pp. 868–878, 2013.
In: 2012 IEEE International Conference on Communications (ICC), pp. 6188–6192, IEEE 2012.
In: 2011 50th IEEE Conference on Decision and Control and European Control Conference, pp. 255–260, IEEE 2011.