Using data driven methods from statistics and machine learning, my work lies at the intersection between social science and computer science.
Recently, I have been working quite a bit with neural networks to study data privacy and institutions in governance. Some of my projects have had a particular focus on Latin America.
You can read about my findings in the Journal of Politics, International Interactions or the Journal of Politics in Latin America.
February 2020: I will be joining the Social Science Foo Camp at Facebook HQ in Menlo Park. Look out for my lightning talk on differentially private synthetic data.
March 2020: Elliott Ash is organising a workshop on AI (for) Governance in Lausanne. Looking forward to present our benchmark for differentially private synthetic data to practitioners and researchers.
March 2020: Polmeth is coming to Europe! Check out the dedicated homepage to know more about our preparation for the first edition.
March 2020: I will be talking at the AI for UK conference at the Turing Institute. The first time we are showcasing our joint project with the National Democratic Institute on detecting voting irregularities analysing satellige images and voting forms using DNNs.
April 2020: Our 3-year research project on developing methods for analyzing political parties’ promises to voters during election campaigns is kicking-off with a first meeting in Gothenburg.
April 2020: Two papers at this year’s 78th Annual MPSA Conference: “Hidden in Plain Sight: Detecting Electoral Fraud Using Statutory Results” and “The Impact of Minimal Participation Rules on Multilateral Cooperation”.