Board members:

Sanne Willems

is Assistant Professor in Applied Statistics in the Methodology & Statistics Unit at Leiden University. Her PhD research focused on finding optimal scaling transformations in GLMs. However, she is now switching to research on the communication of statistics. She studied the interpretation of probability phrases and is working on a project on the use of factchecks to combat misleading graphs.

Nikky van Buuren

holds a master’s degree in Statistical Science (Leiden University). In previous jobs she worked on developing network models, calculation and simulation of financial risks, and programming codes for machine learning frameworks. Nikky is now a Data Scientist for her own company Nidasci, where communication on statistical models is of major importance.

Nynke Krol

is statistical researcher at Statistics Netherlands (Centraal Bureau voor de Statistiek). She holds a master’s degree in Statistical Science (Leiden University), and is former chair of the Young Statisticians. While her day-to-day focus is more on computer languages, a tweet of her brother sparked her interest in the interpretability of human language, and statistics communication.

Laura Verbeek

is a master student in three programs: Biology and Animal Sciences in Wageningen, and Statistical Science in Leiden. After a bachelors’ in Biology in Leiden she decided to focus more on mathematics. She was always interested in science communication and writing for a wider audience, and for a course on Science Journalism she interviewed Sanne about the communication section. After that interview, she never left again.

Ruben Vromans

is an Assistant Professor in the Department of Communication and Cognition at Tilburg University. His research focuses on risk and data communication in healthcare. More specifically, he studies (1) how people think about health risks and how those thoughts influence their health-related decisions and behavior, and (2) how healthcare professionals can best communicate such complex risk information in order to help people make sense of their personalized health risks data and act in ways that benefit their health.

Saar Hommes

is in her last year of her PhD at Tilburg University and the Netherlands Comprehensive Cancer Organization (IKNL). In her research, she deploys natural language generation techniques to convert prediction models to (simple) text that is understandable for patients suffering from severe injuries and cancer patients. Where in high school she was a bit scared of mathematics, she now tries to convince others that statistics isn’t scary and everyone can grow to love it!