AJ (Anne) Sietsma

In my research, I try to find and use machine learning applications for climate change adaptation. Adaptation is about how people respond to the risks posed by climate change. As climate impacts are increasingly becoming clear around the world, researchers and policy makers alike are publishing considerable volumes of reports, analyses and recommendations on adaptation. It is also featured more and more in news reports and social media for example. In addition to the overwhelming volume of data, the variety in all these publications is considerable climate impacts are highly dependant on the local context, which means that adaptation is too. Machine learning methods are one of the few ways to extract useful information from such large and varied datasets.

I am particularly interested in Natural Language Processing (using text as data), including topic modelling and Large Language Models. I use these tools primarily to study policy-related questions. For how do different levels of government cooperate on adaptation? Is there a measurable effect of international agreements? How can we meaningfully measure progress in adaptation?

Before coming to Wageningen, I was a PhD student at the University of Leeds in the UK. I received my MSC in Sustainable Development jointly from the University of Graz and Ca'Foscari University in Venice. As part of this degree, I was an intern at the United Nations Framwork Convention on Climate Change, as well as an exchange student in Basel. Prior to this, I received my BSc in Technology and Liberal Arts & Sciences from the University of Twente, including an exchange to Seoul National University.