Anne Sietsma (he/him)
Throughout my studies, I have been interested in interdisciplinary problems in general, and climate change in specific. In my PhD project, I am exploring the application of machine learning methods for climate change adaptation. More concretely, I am analysing texts, such as scientific papers or policy documents, that are related to adaptation. By using machine learning, we can do this at a scale of thousands of documents. This large scale is important, because it means we can track progress in the field of climate change adaptation as a whole. Identifying trends and regional differences might help decision makers where additional funds are necessary for example.
- Climate change adaptation;
- Big Data (both supervised and unsupervised machine learning);
- Natural Language Processing;
- International policy making;
- Evidence mapping.
- Joint Master Sustainable Development (MSc), Karl-Franzens Universität/Università Ca' Foscari
- Technology and Liberal Arts and Sciences (BSc), University of Twente