I am a Postdoctoral Researcher in the Department of Global Health and Population at the Harvard T.H. Chan School of Public Health, where I work on Bayesian statistical models to predict COVID-19 infections. I am interested in developing and applying methods for evidence synthesis of replications or multiple data sources.
I received my PhD in Bayesian Methodology and Statistics from Utrecht University in 2020. I started my PhD under supervision of prof.dr. Herbert Hoijtink and prof.dr. Irene Klugkist in September 2015 at the [department of Methodology and Statistics] at Utrecht University, funded by an NWO talent Grant ([grant nr: 406-12-001]). This work built on the research for my thesis in the research master program Methodology and Statistics for the Social, Behavioral and Biomedical Sciences, at Utrecht University. In 2015 obtained my MSc with a cum laude distinciton. In my PhD I continued working on Bayesian informative hypothesis testing and focused on Bayesian updating of evidence and knowledge synthesis over multiple single subject datasets. My dissertation The latest update on Bayesian informative hypothesis testing is available here.
During a research visit to prof.dr. Jeff Rouder at University of California, Irvine in 2019, I worked on single case analysis and multilevel approaches to assess whether a theory applies to every case in a population. Throughout my PhD I have applied Bayesian methodology in collaboration with various researchers from literary studies, clinical, developmental and social psychology.
Here you can find an overview of my research, presentations at conferences and workshops, and software I developed.
You can download my complete resume here (version January 2024).