I am an enthusiastic political scientist and (wannabe) data scientist with a great passion for teaching and a strong background in quantitative and qualitative research methods. Throughout my academic journey, I have enjoyed working at diverse institutions in Brazil and the UK, including the University of Brasilia, the Federal University of Rio de Janeiro, the Federal University of Sao Carlos, Queen Mary University, and Aston University. I believe in alternative teaching methods and a more equalitarian education system to foster critical thinking and autonomy.

Beyond academia, I held several managerial positions at the Ministry of Culture of Brazil, becoming a strong advocate for evidence-based policies (although ideologies and politics are inevitable). I worked at the Department of Intellectual Rights and was responsible for international negotiations and monitoring Collective Management Organisations. In addition to providing technical advice to the Ministry of Foreign Affairs, I joined bilateral negotiations directly. I also organised multilateral events, including a meeting for Portuguese-speaking countries in collaboration with the World Intellectual Property Organisation (WIPO). I am passionate about music and literature and have extensive experience working with creative industries.

My previous post-doctoral project led me to a long journey towards data science. Since then, I have focused on programming languages and their application to social science applied research, especially to make better public decisions. I chair the International Political Science Association’s research committee on politics and business and was a co-editor of the Agenda Politica (Political Agenda) journal.

In my spare time, I am a convict nerd, a huge Star Wars fan, a non-talented dancer, and a kickboxing fighter.

A combination of data-driven and theory-driven approaches

This repository combines data-driven and theory-driven approaches for researching politics and policymaking. In the era of artificial intelligence, it is crucial to use computational methods to enhance our research techniques and make better decisions regarding public policies. Hence, my research interests encompass scientific methodology, public administration, political governance, and public policies. I seek to use data science techniques to investigate policy issues and help policymakers make better decisions based on data. As a researcher, I combine a strong background in political theory with data science skills. I develop and change political concepts based on data analysis and design data collection and analysis based on theories in a eternal interative process.

A dynamic and equalitarian perspective of teaching

This page also offers resources for researching and teaching data science and political science. The page “research and resources” contains all the repositories linked to my previous research projects. In teaching, you will find the links to the syllabus and descriptions of the modules I led. I believe in a dynamic and equalitarian teaching perspective, where students have the autonomy to develop critical thinking. I do not believe in strong social hierarchies. My role as a lecturer is similar to that of a facilitator. My teaching methodology includes practical and interactive exercises combining political science with my students’ hobbies, e.g. political analysis of TV shows and pop culture. I am also able to use different media. I always support my students in their endeavours.

Disclaimer: This page used the template made by academicpages.github.io. Copyright (c) 2016 Michael Rose