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Teaching and supervision

PhD students

Tijn Jacobs, 'High-dimensional Bayesian causal inference in the potential outcomes framework'.

Nadja Rutsch, 'High-dimensional Bayesian causal inference with DAGs'.

Kayané Robach, `Causal record linkage'.

Julia Kowalska, `Bayesian theory and methods for the regression discontinuity design'.

Máté Kormos, `Mathematical statistical theory for causal inference’.
Jan Jaap de Graeff, `Novel research methodology and evaluation of orthopaedic standard of care’.
Bart Eggen, `Bayesian sensitivity analysis for causal inference’.


2022: Martin Kroon, `Towards the automatic detection of syntactic differences.’  Thesis.


Zhongyi Hu, postdoc in the BayCause project.

Bachelor/master theses

Master theses

Daniel Gomon (2021). Continuous time control charts: generalizations and an application to the Dutch Arthroplasty Register (LROI). Winner Best Thesis in Applied Math Award 2021.
Caroline Kok (2019). A mathematical comparison and improvement of statistical control charts in medical contexts.

Bachelor theses

Stijn van Eig (2020). Variance estimation by bootstrap in nearest neighbour propensity score matching with replacement.
Pascal van der Vaart (2019). Statistical methods for quantum state estimation.
Sebastiaan Draijer (2018). Correlatie en causaliteit: failliet door de pinpas?
Daniel Gomon (2017). Horseshoe prior: robustness against non-normal deviations.
Arjun Harinandansingh (2016). Meervoudig toetsen met de horseshoe prior.
Rens Geerling (2015). Community detection in networks.
Fréderique Kool (2014). Een statistische analyse van recidive-cijfers.
Jason Zijlstra (2014). An exploration of exoplanetary transit detection algorithms.


Modelleren (at MI, Leiden University); 2019, 2020.
Inleiding Mathematische Statistiek (at MI, Leiden University); 2017, 2018, 2019, 2020.
AWV2 (at LUMC); 2017.
Statistics (at LUC); 2015, 2016.
Numeracy (at LUC); 2013, 2014.

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