Wouter van Loon
Guest
- Name
- W.S. van Loon MSc
- Telephone
- +31 71 527 2727
- w.s.van.loon@fsw.leidenuniv.nl
- ORCID iD
- 0000-0002-4701-9265
Short CV
Wouter van Loon is a PhD candidate at the department of Methodology and Statistics and the Leiden Centre of Data Science (LCDS). He obtained his Master’s degree in Statistical Science (cum laude) at Leiden University. His research primarily concerns supervised learning algorithms for combining information from different types of high-dimensional data.
Research
The aim of his PhD project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data. Nowadays, researchers are confronted with multi-domain data more and more often. In health research, for example, multi-domain data can occur 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 domains can potentially lead to improved early diagnosis of disease. Furthermore, identification of important domains can lead to simpler, more interpretable diagnostic models.
This project is part of the Data Science Research Programme.
Teaching
Wouter is a tutorial instructor for the second-year bachelor course on Multivariate Data Analysis.
Supervisors
Relevant links
Guest
- Faculteit der Sociale Wetenschappen
- Instituut Psychologie
- Methodologie & Statistiek
- Loon W.S. van, Fokkema M., Rooij M.J. de & Szabo B.T. (2024), View selection in multi-view stacking choosing the meta-learner: choosing the meta-learner, Advances in Data Analysis and Classification (2024): .
- Loon W.S. van, Fokkema M., Szabo B. & Rooij M.J. de (2024), View selection in multi-view stacking: choosing the meta-learner, Advances in Data Analysis and Classification : .
- Wiggers G., Verberne S., Loon W.S. van & Zwenne G.J. (2023), Bibliometric‐enhanced legal information retrieval: combining usage and citations as flavors of impact relevance, Journal of the Association for Information Science and Technology 74(8): 1010-1025.
- Loon W.S. van, Vos F. de, Fokkema M., Szabo B.T., Koini M., Schmidt R. & Rooij M.J. de (2022), Analyzing hierarchical multi-view MRI Data With StaPLR An Application to Alzheimer's disease classification: an application to Alzheimer's disease classification, Frontiers in Neuroscience 16: 1-36 (830630).
- Wiggers G., Verberne S., Zwenne G.J. & Loon W.S. van (2022), Exploration of Domain Relevance by Legal Professionals in Information Retrieval Systems, Legal Information Management 22(1): 49-67.
- Loon W.S. van, Fokkema M. & Szabo B.T. Rooij M.J. de (2020), Stacked penalized logistic regression for selecting views in multi-view learning, Information Fusion 61: 113-123.