I am a Research Scientist in the AI & Economics lab at Spotify. My research interests are broadly in causal inference and data-driven decision-making in digital and technology-mediated systems, such as online platforms, digital health, and digital media. Most of my work develops methods for applied research and practice, grounded in econometrics, machine learning, and optimization. At Spotify, I work on how to make experimentation, evaluation, and personalization more efficient and effective, most recently when it is augmented with AI.

I received my PhD from D-MTEC at ETH Zurich in 2024, advised by Stefan Feuerriegel and Florian von Wangenheim. My thesis was on methods and applications for causal machine learning. During my doctorate, I visited the Operations, Information, and Technology group at Stanford GSB, hosted by Jann Spiess, and interned as a Research Scientist at Booking.com. I also contribute to the nonprofit Algorithm Audit.

I hold master's and bachelor's degrees in Statistics and Business & Economics from Lund University, Sweden. Before my PhD, I worked in marketing science at GfK (acquired by NielsenIQ) and in performance marketing at Precis Digital.