Michael Ganslmeier

Michael Ganslmeier is an Assistant Professor in Computational Social Science at the University of Exeter. He holds a PhD from Oxford, a master's from LSE, and a bachelor's from Zeppelin University, with additional coursework at Columbia University. His research focuses on causal inference, machine learning, and computational methods applied to political behavior, climate policy, and pandemic response. He collaborates with institutions like the World Bank and IMF, addressing issues such as climate policy feasibility and economic impacts of weather patterns.

• Affiliations: University of Exeter (since 2024), World Bank (consultant since 2023), LSE (Postdoc Fellow 2022-24).
• Education: PhD, University of Oxford; MSc, LSE; BSc, Zeppelin University (with a semester at Columbia).

Research interests include political economy, public opinion dynamics, and geospatial data analysis. He has published in high-impact journals like Proceedings of the National Academy of Sciences and Scientific Reports, focusing on topics such as lockdown compliance during the pandemic and the political costs of climate policies. His teaching spans causal inference, data science, and computational programming at both undergraduate and graduate levels.

Key collaborations include projects on climate policy feasibility with the World Bank and IMF, as well as research on aging populations' economic impacts. He is skilled in programming languages (R, Python, SQL) and tools like TensorFlow and ArcGIS.