Computational Social Scientist

I'm Javier, an assistant professor at Utrecht University in the Social Data Science (SoDa) team Before that, I was a postdoc at the University of Amsterdam and at Charles University (CORPTAX), and a data scientist at the Tax Justice Network. In my research I apply computational models to understand social and economical systems. I completed my PhD in Political Economy at the CORPNET group (University of Amsterdam), and my MSc in Computer Science at the Univerity of Vermont.

Research interests:

  • (1) Computational social science: Polarization and inequality.
  • (2) Political economy: Corporate networks, tax avoidance, corporate power.
  • (3) Biological Complex Systems: Stochasticity in genetic networks and single-cell dynamics.
  • (4) Data science: Web Scraping, machine learning, data visualization.

Publications and Research Overview

I'm planning to add a complete list of paper here, together with their data/code. For now check my Google Scholar page. You can always email me for requests about data, code, teaching or consultancy.


Check out my CV in PDF or Overleaf

Academic Career

Assistant Professor in Social Data Science

Oct 2021 - Present

Utrecht University, the Netherlands

Computational modeling of social and behavioral systems.

PostDoc in Social Complexity

June 2021 - Oct 2021

University of Amsterdam, the Netherlands

Computational modeling of social and behavioral systems.

PostDoc in Economics

Jan 2021 - Oct 2021

Charles University, Prague, Czechia (Remote)

Modeling the scale and drivers of corporate tax avoidance.

PhD in Computational Political Economy

2015 – 2020

University of Amsterdam, the Netherlands

Computational modeling of the relationships between tax haves and corporations.

MSc in Computer Science

2013 – 2015

The University of Vermont, United States

Computational modelling of genetic networks and single-cell dynamics, and of social conflict.

BSc in Biotechnology

2007 – 2012

The University of León, Spain


Data Scientist at the Tax Justice Network

2019 – 2021


  • Data visualizations.
  • Workflow automation.
  • Research on illicit financial flows.


2019 – Present
  • The International Monetary Fund (IMF)
  • The International Centre for Tax and Development (ICTD)
  • SEO Amsterdam Economics
  • The Organisation for Economic Co-operation and Development (OECD)


Click on the titles to access the materials

Working with data (full course)

Introduction to data science with Python/Pandas/Seaborn for research master students of social science (2019, 2018 and 2017).

Introduction to R (2-day workshop)

Introduction to data science with R.

Web scraping workshop

Introduction to web scraping using Python, including basics of HTML, APIs, and the requests and selenium libraries (several venues).

Data visualization workshop

Introduction to data visualization, focused on academic visualization.

Text analysis workshop

Introduction to sentiment and topic modeling

String matching and database merging

Machine Learning to compare and join heterogeneous data from heterogeneous sources.


Get in touch

  • Office: Utrecht University, Department of Methodology & Statistics, Heidelberglaan 8 3584 CS Utrecht, the Netherlands
  • Email: j.garciabernardo (at) uu (dot) nl
  • CV: PDF or Overleaf
  • Github
  • Google Scholar