Biography
Xavier Fernández-i-Marín is Social Sciences methodologist, currently serving as ”Ramón y Cajal” fellow at the Universitat de Barcelona. He develops and tailors solutions for social science research methods, including current developments in Bayesian inference, data visualization, probabilistic programming, experimental designs and machine learning. He has substantial contributions in comparative politics, public administration, public policy, international relations and psychology. He has worked in the fields of global governance and IGOs, the diffusion of policies and institutions and the processes of development of regulatory agencies. Also, he worked on Internet and e-Government diffusion and other related aspects of the public management of the Information Society, which lately include the adoption of Artificial Intelligence in public administration. He has been trained in methodology at the University of Essex, obtaining a postgraduate degree, and teaching in the summer school for several years. He has ample experience with hierarchical/multilevel models and bayesian inference, and also in cluster analysis, principal component analysis, factor analysis, survival (event history) analysis, spatial models and quantitative methods in general, as well as with experimental designs and text analysis. This has brought collaborations with several disciplines, bringing scientific, methodological and systematic value to different teams. He is the creator and developer of several R packages, including ggmcmc[6], an R package for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis; and PolicyPortfolios, to work with data on comparative public policy.
1J Measurement: From simple classification to model estimation
