Udo Böhm

I am postdoc in the Machine Learning Group at CWI (national research institute for mathematics and computer science) and a teacher at the Psychological Methods Unit at the University of Amsterdam. I received my PhD in Mathematical Psychology in 2018 from the University of Groningen. My work focusses on the development of computational and statistical (mostly Bayesian) methods for evidence accumulation models.

During my PhD I investigated how environmental factors such as time pressure and reward structures should be accommodated in diffusion models of perceptual decision-making. In this context I also developed hierarchical Bayesian methods for parameter estimation and model comparison. My postdoctoral research aims to extend this statistical framework to ballistic evidence accumulation models, and to develop off-the-shelf solutions for applying evidence accumulation models to ANOVA and regression-type experimental designs.

Publications by Udo Böhm