L. V. Heydebreck
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
L. V. Heydebreck has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
A.-L. Rau
Center of Methods, Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications- C. Krügermeier
Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications C. Schwenck
Center of Methods, Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications- Charlotte Gohr
Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications - D. Berg-Moelleken
Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications - E. Frank
Center of Methods, Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany
2 shared publications
Latest Publications
- Open Access
- 2 September 2025
- Published by Springer Nature in Nature Sustainability
- Vol. 8 (11) , 1408
Author Correction: Artificial intelligence in sustainable development research
- 2 September 2025
- Published by Springer Nature in Nature Sustainability
- Vol. 8 (11) , 1408
Open AccessAuthor Correction: Artificial intelligence in sustainable development research
- Top Cited PapersOpen Access
- 21 July 2025
- Published by Springer Nature in Nature Sustainability
- Vol. 8 (8) , 970-978
Artificial intelligence in sustainable development research
Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI’s transformative role in sustainable development are high, its full potential remains to be realized.
- 21 July 2025
- Published by Springer Nature in Nature Sustainability
- Vol. 8 (8) , 970-978
Top Cited PapersOpen AccessArtificial intelligence in sustainable development research
Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI’s transformative role in sustainable development are high, its full potential remains to be realized.