I am an Assistant Professor of Statistics at the Business Analytics Section of the University of Amsterdam. As a statistician and data scientist, my research interests lie in developing efficient computational methods for inference and learning from high-dimensional multivariate data that routinely arise in econometrics, machine learning, neuroscience, and health care. My current research is focused on developing Bayesian statistical methods in graphical models for multivariate statistical analysis to understand the underlying mechanisms in complex systems. These methods have a wide range of applications, such as health care to capture brain connectivity to treat Alzheimer's. 

Short Bio

I joined the Business Analytics Section of the University of Amsterdam as an Assistant Professor in November 2017. During 2016-2017, I worked as a postdoctoral researcher as a statistician at the Department of Methodology and Statistics at the Tilburg University and Jheronimus Academy of Data Science (JADS). In 2015, I received my Ph.D. in Statistics from the University of Groningen, my thesis entitled: Bayesian Model Determination in Complex Systems.

I am a core developer of the following open source software which are used in my publications:

• R package BDgraph: Bayesian Structure Learning in Graphical Models using Brith-Death MCMC;
• R package ssgraph:   Bayesian Graphical Estimation using Spike-and-Slab Priors;
• R package bmixture: Bayesian Estimation for Finite Mixture of Distributions;
• R package liveR:         Eating the Liver of Data Science.