My name is Joris Mulder. I work as an associate professor at the Department of Methodology and Statistics at Tilburg University and the Jheronimus Academy of Data Science. In my research I develop Bayesian statistical methods for applications in the social, behavioral, and medical sciences. I am active on the following research themes.
- Dynamic social network modeling. Currently my main line of research is on Bayesian modeling of relational event histories, i.e., data that contain information about who interacted with whom at what time. The goal is to develop methods that allow us to better understand how interaction dynamics in a social network change over time based on these types of data. This work is supported by an ERC Starting Grant and a NWO Vidi Grant. I work on this topic together with Roger Leenders, Peter Hoff, Marlyne Bosman-Meijerink, Giuseppe Arena, Diana Karimova, and Mahdi Shafiee Kamalabad, among others.
- Bayes factor hypothesis testing. An other line of research focusses on developing default Bayes factors for testing (informative) hypotheses with equality and/or order constraints on the parameter of interest. These have been implemented in different software packages such as BIEMS, BCT, bain, and BFpack. These have been developed together with Herbert Hoijtink, Xin Gu, Florian Böing-Messing, among others.
- Other topics that I am currently working on are Bayesian regularization, Bayesian structural equation modeling, (together with Sara van Erp and Daniel Oberski, supported by a NWO Talent Grant), Bayesian clinical trial designs (together with Xynthia Kavelaars and Maurits Kaptein, supported by a NWO Talent Grant), Bayesian network autocorrelation modeling (together with Roger Leenders, Dino Dittrich, and Carter Butts), and Gaussian Graphical Models (together with Donald R. Williams).
If you want to share your ideas or thoughts or if you have any questions about my work, feel free to email me at: j [dot] mulder3 [at] tilburguniversity [dot] edu.