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Paul Hün­er­mund

Associate Professor

Subjects
Statistics Managerial economics Innovation Artificial intelligence Machine learning Qualitative methods

Primary research areas

I study how firms use new tech­no­lo­gies to in­nov­ate and com­pete.

My research helps firms and policymakers understand how emerging technologies—such as artificial intelligence, machine learning, and other digital innovations—can create value, foster innovation, and support sustainable growth. I study how organizations can leverage these technologies while avoiding biases in decision-making, enabling more effective strategies in highly competitive environments.

I also examine how public R&D policies can be designed and evaluated to stimulate innovation and economic progress. This work provides actionable insights for decision-makers and has informed institutions such as the European Commission, the German Federal Ministry of Research and Education, and the OECD.

Beyond academia, I co-founded causalscience.org, a platform connecting industry and academia on causal data science. My ambition is to bridge rigorous research with real-world applications, contributing to economic growth, technological progress, and environmental sustainability.