Torben Johansen

Torben Johansen is an Assistant Professor in the Department of Economics VIP at the University of Southern Denmark. His research focuses on machine learning applications in historical data analysis, econometrics, and causal inference. He actively collaborates on projects combining machine learning with socioeconomic data, such as improving census transcriptions and analyzing breastfeeding impacts on educational outcomes. Johansen teaches courses in statistics and historical economics applications, supervises master’s students in economics and medicine, and engages in academic activities through conferences and peer reviews. His work bridges computer science and social sciences, with notable contributions to occupational standardization and policy optimization. He has contributed datasets to platforms like Harvard Dataverse and engages in public discourse on child health policies.

• Education: Implied PhD in Economics or related field (not explicitly stated)

Research Interests: Machine Learning in socioeconomic contexts, causal inference, historical data digitization, and health economics. His methodologies include neural networks, transfer learning, and optimization algorithms applied to real-world policy problems.

Recent research trends emphasize interdisciplinary approaches, blending econometric models with machine learning to address challenges in healthcare, labor markets, and historical record analysis. Key contributions include improving transcription accuracy in historical censuses and evaluating long-term effects of early childhood health interventions.

• Awards: None explicitly mentioned

Advising involves supervision of master’s students in economics and medicine. His teaching portfolio includes applied statistics and historical perspectives on economics. Grants and funding details are not detailed in the provided text.

Labs/Teams: Active member of the HEDG (Historical Economics & Development Group) and collaborates with researchers in computer science and public health.