Lecturer in Statistics
Programme Director Graduate Certificate/Diploma in Statistics
Department of Economics, Mathematics and Statistics
Birkbeck, University of London

Office 738, Malet Street, Bloomsbury
London WC1E 7HX
United Kingdom

Email address: i.gollini@bbk.ac.uk

Links: Academic WebsiteResearch Gate | Linkedin | Google Scholar | Github

June 21-23, 2017
Birkbeck, University of London, UK

Recent/Upcoming Events

 12-14 Jul 2017
Invited Talk at Data Science, Statistics & Visualisation, Lisbon, Portugal
 4-7 Jul 2017
Keynote Lecture at useR!2017, Brussels, Belgium. [Video and Slides]
 28-29 Jun 2017 Short Course on Statistical Social Network Analysis with R, University of Padua, Italy
 14 Jun 2017 Seminar at Stochastic Processes Group, University College London, UK
 16-17 May 2017 Invited Talk at 6th International Workshop on Social Network Analysis, Naples, Italy
 11 May 2017 Seminar at Department of Mathematical Sciences, University of Essex, UK
 10-12 Apr 2017 Short Course on Statistical Social Network Analysis, University of Bologna, Italy
 14 Feb 2017 Seminar at School of Computer Science and Statistics, Trinity College Dublin, Ireland
 13 Feb 2017 Talk at  Working Group on Statistical Learning, University College Dublin, Ireland

My research activity aims to integrate statistical methods with various applications through cross-disciplinary collaborations. As an applied statistician I have been working closely with scientists with different expertise (e.g. engineers, geographers, computer scientists, etc.) in order to yield important practical results as well as developments of new statistical techniques.

During my research activity in UK and Ireland I worked on the development of original methodologies and gathered a broad experience in analyzing different types of data. 

At the University of Bristol, I worked on statistical methods for assessing uncertainty and risk in natural hazardsAt Maynooth University I worked on regression models for spatial data. During my PhD studies at the University College Dublin I developed latent variable models to summarize and visualize multiple information in biological and social networks and cluster complex categorical data. These methods find application in a wide range of research areas including social sciences, health sciences and marketing.

I am interested in teaching methods and tools to promote diversity in the Statistics, Data Science and R communities for this reason I am mentor at R-Ladies and leader of the teaching team at Forwards the R Foundation taskforce on women and other under-represented groups.