Torben S. D. Johansen

Torben S. D. Johansen

Assistant Professor at University of Southern Denmark

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

publications

Applications of machine learning in tabular document digitisation

Published in Historical Methods: A Journal of Quantitative and Interdisciplinary History, 2023

Recommended citation: Dahl, Christian M., Torben S. D. Johansen, Emil N. Sørensen, Christian E. Westermann, and Simon F. Wittrock (2023). “Applications of machine learning in tabular document digitisation”. In: Historical Methods: A Journal of Quantitative and Interdisciplinary History 56.1, pp. 34–48. doi: 10.1080/01615440.2023.2164879. https://www.tandfonline.com/doi/abs/10.1080/01615440.2023.2164879

Low-dose naltrexone for treatment of pain in patients with fibromyalgia: a randomized, double-blind, placebo-controlled, crossover study

Published in PAIN Reports, 2023

Recommended citation: Bested, K., Jensen, L. M., Andresen, T., Tarp, G., Skovbjerg, L., Johansen, T. S. D., Schmedes, A. V., Storgaard, I. K., Madsen, J. S., Werner, M. U., and Bendiksen, A. (2023). Low-dose naltrexone for treatment of pain in patients with fibromyalgia: a randomized, double-blind, placebo-controlled, crossover study. PAIN Reports, 8(4), e1080. https://journals.lww.com/painrpts/Fulltext/2023/08000/Low_dose_naltrexone_for_treatment_of_pain_in.3.aspx

Duration and intensity of being breastfed and educational attainment, income and labour force participation: a prospective cohort and sibling study from Denmark

Published in Public Health, 2024

Recommended citation: Bjerregaard, L. G., Johansen, T. S. D., Dahl, C. M., & Baker, J. L. (2024). Duration and intensity of being breastfed and educational attainment, income and labour force participation: a prospective cohort and sibling study from Denmark. Public Health, 237, 37-43. https://www.sciencedirect.com/science/article/pii/S003335062400372X

Inflammatory biomarkers as prognostic tools for diabetic retinopathy progression: a prospective study

Published in Diabetes Research and Clinical Practice, 2026

Recommended citation: Johansen, M. S., Stidsen, J. V., Hansen, A. L., Johansen, T. S. D., Nielsen, J. S., Pedersen, F. N., Grauslund, J., Olsen, M. H., Højlund, K., & Olesen, T. B. (2026). Inflammatory biomarkers as prognostic tools for diabetic retinopathy progression: a prospective study. Diabetes Research and Clinical Practice, 235, 113195. https://doi.org/10.1016/j.diabres.2026.113195

DARE: A large-scale handwritten DAte REcognition system

Published in International Journal on Document Analysis and Recognition (IJDAR), 2026

Recommended citation: Dahl, Christian M., Torben S. D. Johansen, Emil N. Sørensen, Christian E. Westermann, and Simon F. Wittrock (2026). “DARE: A large-scale handwritten DAte REcognition system”. In: International Journal on Document Analysis and Recognition (IJDAR). doi: 10.1007/s10032-026-00587-5. https://link.springer.com/article/10.1007/s10032-026-00587-5

talks

Essen Health Conference 2022

Published:

Presented the paper “Universal Investments in Toddler Health: Learning from a Large Government Trial”.

Human Capital in the Nordic Countries group

Published:

Presented my work on transcription of Danish censues as part of the Link-Lives project during an informal meeting of the HCNC group. Joint presentation with Nicolai Rask Mathiesen.

Department Forum on AI

Published:

Presented my work on large-scale transcription at the Department Forum on AI, Department of Regional Health Research, at University of Southern Denmark. Invited talk.

Annual Meeting of the Danish Econometric Society

Published:

Presented my work on transcription of the “Copenhagen Health Visitor Record”, used in projects such as the paper “Universal Investments in Toddler Health: Learning from a Large Government Trial”, alongside some more method-heavy large-scale transcription work.

Data Science Paper Review and Chat

Published:

Presented my work on transcription at a “Data Science Paper Review and Chat” weekly data science meeting of Findmypast. Invited talk.

Department Seminar

Published:

Presented my work on large-scale transcription at a department seminar at Lund University. Invited talk.

D3A 2.0

Published:

Presented methods in causal machine learning in the session “Supercharge Your Causal Inference with Machine Learning” together with Alexander O. K. Marin, Phillip Heiler, and Nadja van ‘t Hoff. Session organizer.

EHS Annual Conference

Published:

Presented the project “Improving Historical Census Transcriptions: A Machine Learning Approach”.

Nation Scale Lunch Seminar

Published:

Presented the project “Optimal Treatment Allocation Under Constraints”. Invited talk.

Social Science History Association

Published:

Invited as panelist to the session “Complexity, Consequences, and Best Practices for AI in Historical Social Science Research and Data Development”.

EHS Annual Conference

Published:

Presented the project “Improving Historical Census Transcriptions: A Machine Learning Approach”.

Department Seminar

Published:

Presented the project “Group-Level Treatment Effect Heterogeneity in Difference-in-Differences: A Balanced Approach”. Invited talk.

Department Seminar

Published:

Presented the project “Group-Level Treatment Effect Heterogeneity in Difference-in-Differences: A Balanced Approach”. Invited talk.

teaching

Microeconometrics

TA, master level course, University of Southern Denmark, 2019

Course for the Economics master’s program (10 ECTS).

Regression Analysis

Guest Lecturer, bachelor level course, University of Southern Denmark, 2019

Course for the Economics bachelor’s program (10 ECTS).

Applied Machine Learning

Lecturer, master level course, University of Southern Denmark, 2020

Course for the Data Science master’s program (10 ECTS). The course covers support vector machines, random forests, boosting, and deep learning, with an emphasis on deep learning. The goal is to give students the ability to confidently apply state-of-the-art machine learning methods to a broad class of problems, including computer vision and natural language processing.

Applied Machine Learning

Guest lecturer, master level course, University of Southern Denmark, 2023

Course for the Data Science master’s program (10 ECTS). The course covers support vector machines, random forests, boosting, and deep learning, with an emphasis on deep learning. The goal is to give students the ability to confidently apply state-of-the-art machine learning methods to a broad class of problems, including computer vision and natural language processing.

Applied Statistics

Lecturer, bachelor level course, University of Southern Denmark, 2024

Course for the GMM engineering bachelors’s program (5 ECTS). The course cover introductory statistics, including probability theory, confidence intervals, hypothesis testing, linear regression analysis, factor analysis, and cluster analysis. The goal is to give students the ability to confidently perform and interpret statistical analyses.

Statistics

Lecturer, bachelor and master level course, University of Southern Denmark, 2024

Course for the PDI engineering bachelors’s and master’s program (5 ECTS). The course cover introductory statistics, including probability theory, confidence intervals, hypothesis testing, linear regression analysis, factor analysis, and cluster analysis. The goal is to give students the ability to confidently perform and interpret statistical analyses.

Machine Learning in Economics & Finance

Lecturer, master level course, University of Southern Denmark, 2025

Elective course for the economics master’s program (10 ECTS). The aim of this course is to enable students to use state-of-the-art methods in machine learning, including their applications in economics and finance.

Regression Analysis

Lecturer, bachelor level course, University of Southern Denmark, 2025

Course for the Economics bachelor’s program (10 ECTS).

Machine Learning in Economics & Finance

Lecturer, master level course, University of Southern Denmark, 2026

Elective course for the economics master’s program (10 ECTS). The aim of this course is to enable students to use state-of-the-art methods in machine learning, including their applications in economics and finance. Awarded Teacher of the Year (DKK 40,000) by the Faculty of Social Sciences, University of Southern Denmark (2026).

Regression Analysis

Lecturer, bachelor level course, University of Southern Denmark, 2026

Course for the Economics bachelor’s program (10 ECTS).