I am currently based at the Computer Science Department of University College London. My primary research focus is the transformation of user-generated content created by online activity (social media, search queries etc.) to collective or personalised inferences as well as enhanced interpretations of human behaviour. I am therefore interested in interdisciplinary research tasks that can bring together the areas of Artificial Intelligence, Statistics and Natural Language Processing with various aspects in the domains of Health, Social Sciences and Economics.
Recent news snippets
- [14/04/2017] Consider submitting your research to the JMIR's Special Issue on Mining Online Health Reports that I am co-editing. The deadline is June 15, 2017.
- [01/01/2017] Our paper on improving feature selection for the task of influenza-like illness monitoring from search query data has been accepted by WWW 2017.
- [24/10/2016] Our paper on predicting judicial decisions of the European Court of Human Rights using statistical NLP was published in PeerJ Computer Science. Partial aspects of the results have been covered by mainstream media outlets (VICE, BBC, The Guardian and so on) and a UCL press release.
- [08/09/2016] I am co-organising a WSDM 2017 Workshop on Mining Online Health Reports. Submission deadline: 11/11/2016
- [06/09/2016] I am giving a lecture at the "Big Data and Networks in Social Sciences" summer school (September 21-23 at the University of Warwick). Registration is free.
- [03/08/2016] Some of my recent research outcomes have been featured by the EPSRC
- [14/04/2016] We have launched a beta version of our Flu Detector that uses Google search query data to monitor influenza-like illness rates in England (the inference method is based on this paper)
- [11/04/2016] Presentation of our paper on infectious intestinal disease surveillance from social media (Digital Health conference at WWW '16)
- [08/03/2016] Invited talk and guest lecture at the University of Copenhagen
- [05/12/2015] Paper that proposes a method for inferring the socioeconomic status of social media users was accepted at ECIR 2016 [poster]