Scalable Estimation for Popularity-adjusted Latent Space Models for Network Data

In network modelling, edges are inherently interdependent: for instance, if you express interest in this project and contact me, it is more likely that a friend of yours, specifically one who shares similar interests and studies mathematics, will do the same. This interdependence complicates the statistical modelling of relational data, such as email communication networks. … Read more

Inside Airbnb: Tourism in Dublin (taken)

In the last decade, Airbnb has become a mainstay for tourists worldwide. In this project, we will use data from insideairbnb.com to obtain a better geographic understanding of Dublin. Which parts are expensive or reasonable to rent? Where do tourists like to stay, and in what type of accommodation? We will study these issues using … Read more

To interpret or not to interpret: Forecasting conflict fatalities with machine learning models vs. GLMs

Forecasting conflict on a fine-grained grid level has real-life policy implications that can empirically inform meaningful healthcare and peace-preservation decisions. In many settings, interpretable models have the appeal that policymakers know how to draw conclusions from the model and do not have to base their decisions on black-box models. On the other hand, machine learning … Read more