About
I am a postdoc and research software engineer in the Bayesian Workflow Group at Aalto University, Finland, where I implement new developments in Bayesian statistics in open-source software, primarily within the Stan ecosystem. My work spans method development, end-to-end data and modelling workflows, and the development of open, well-tested research software in Python and R.
Previously, I built greenhouse-gas concentration data pipelines at Climate Resource GmbH and completed a doctorate in computational statistics at TU Dortmund University on simulation-based expert prior elicitation (elicito).
Background
My path into research software engineering began in applied psychology. During my bachelor’s in Business Psychology I focused on consumer and market research, with first practical experience at Ipsos GmbH and Produkt+Markt GmbH. To deepen my computational and statistical skills, I followed up with a master’s in Cognitive Science with a focus on machine learning, formal modelling, Bayesian methods, and their implementation in R and Python.
In academia, I worked at Philipps-University Marburg, the SimTech Cluster of Excellence at the University of Stuttgart, and TU Dortmund University, where I completed my doctorate in computational statistics on expert prior elicitation and developed the open-source Python package elicito. In the final year of my PhD, I also joined Climate Resource as a research scientist and software engineer, developing data pipelines for Earth system modelling groups. I am now at Aalto University, working at the intersection of Bayesian methods, research software engineering, and reproducible science.