Hi! I'm Rickard, a scientist and engineer with a focus on causal inference and machine learning. I'm drawn to problems where getting the answer right actually matters, and where off-the-shelf methods tend to fall short.

I recently completed my PhD in Computer Science (cum laude) at TU Delft, with stints at Harvard and Booking.com. The core question I worked on was how to better answer causal questions from data, particularly by combining randomized controlled trials with observational data using flexible machine learning models. The goal was to make causal conclusions both more reliable and less dependent on having large amounts of data.

I'm originally from Sweden, where I did my BSc in Engineering Physics and MSc in Engineering Mathematics at Chalmers University of Technology. During my studies I also interned at NASA Goddard Space Flight Center.

As part of my research, I've also developed several open-source tools. These include causal-falsify, a Python package implementing methods to detect unmeasured confounding in observational data, and rct-checker, an LLM-based tool that automatically extracts table data from medical papers on randomized controlled trials and checks for statistical irregularities.