Data Science

Why clustering, embeddings, and latent representations matter for studying education, culture, organizations, mobility, and collective behavior.

What the EPJ Data Science paper on insecurity and urban mobility says about gender, safety, and daily movement.

Crime and violence shape perceived insecurity in cities, but their consequences are not gender neutral. This article links perceived …

Course on complex networks, graph analytics, null models, communities, diffusion, and graph machine learning.

Course on clustering, dimensionality reduction, representation learning, topic models, anomaly detection, embeddings, and unsupervised workflows for behavioral and social data.

Public procurement markets are highly structured networks. Using over one million Portuguese public procurement contracts, this article …

The UDD Data Science Institute profiled CRiSS-LAB as a laboratory studying collective intelligence, collective memory, online engagement, education, and applied tools such as Capybara and Lixandria.

Course module on causal questions, identification, quasi-experiments, observational data, and policy evaluation.

Abstract: [ENG] We discuss two projects that quantify the consequences of our network location for our access to resources and rewards in science. First, we investigate the dynamics of international science through the lens of national citation preferences, introducing a novel measure to characterize these processes and enabling a network analysis of global knowledge production.

Abstract: [ENG] It is well known that social networks fundamentally impact the dynamic processes of the populations they support. Examples include epidemic outbreaks, the diffusion of innovations, opinion formation, and behavioral evolution.

Funded by CINS-DATA Spa. 2022.

Funded by Universidad del Desarrollo. 2022-2023.

Funded by Derco. 2021-2022.

Funded by ANID, Fondef IDea I+D 2019, ID19I10413. 2019-2022.