WOUTER VAN LOON
Email
w.s.van.loon@fsw.leidenuniv.nl
Website
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Wouter van Loon was a Visiting Scholar at the QUT node of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) from September 2022 to January 2023.
Wouter is a PhD candidate at Leiden University, the Netherlands. His current research primarily concerns multi-view machine learning, which is the integration of data from different sources, modalities, or domains (typically called ‘views’) through machine learning methods. In particular, he works on developing interpretable supervised learning algorithms for combining information from different types of high-dimensional data.
Such data occurs in, for example, biomedical research when data are collected from multiple sources (e.g. medical imaging, genomics, questionnaires), or when different feature sets are derived from a single source (e.g. different MRI modalities).
Combining data from multiple views can potentially lead to improved early diagnosis of disease. Furthermore, identification of important views can lead to simpler, more interpretable diagnostic models.
In addition to his own work on multi-view machine learning, he has also worked as a statistician for research projects in the fields of legal information retrieval and bias in social media.