Hi, and welcome to my website.

I am a Research Scientist at Spotify, since the start of 2024. My research focuses on how to optimize personalization, experimentation and decision-making from data in digital domains. Methodologically, my interests span causal inference, machine learning, econometrics, contextual bandits, reinforcement learning, and statistical decision theory. More recently, I have begun working on how to improve the training and evaluation of recommender systems powered by AI.

I hold a PhD from the Department of Management, Technology, and Economics at ETH Zurich, where I studied causal inference, machine learning, and data-driven decision-making in digital healthcare, digital marketing, and online platforms. My supervisors were Stefan Feuerriegel and Florian von Wangenheim. During my PhD, I visited the Operations, Information & Technology area at Stanford Graduate School of Business, hosted by Jann Spiess, and interned as Machine Learning Researcher at Booking.com in Amsterdam. I also joined Algorithm Audit as a technical contributor, which I continue to be involved in. 

Previously, I obtained double BSc and MSc degrees in Statistics and Business & Economics from Lund University, Sweden, and worked as Marketing Scientist at GfK (now part of Nielsen) and as analyst at an award-winning digital marketing agency.