Short bio

I am a Quantitative Researcher at Nordea Asset Management, where I build ML and AI-driven models for investment research.

Previously, I was a postdoc in machine learning theory at the Department of Mathematics and Computer Science (IMADA), University of Southern Denmark (SDU). Here, I was a member of the Data Science and Statistics (DSS) Group, the Center for Machine Learning (CML), and the Adaptive Intelligence Lab. I was also affiliated with the Pioneer Centre for AI (P1).

I did my Ph.D. in statistics at the Laboratory for Probability, Statistics, and Modeling (LPSM), Sorbonne Université, under the supervision of Antoine Godichon-Baggioni and Olivier Wintenberger; here you can find my manuscript and slides. During the first year of my Ph.D., I also worked part-time at Advestis as an AI Research Scientist.

Research interest

My research focuses on statistical learning theory, with an emphasis on developing adaptive methods for sequential decision-making across stochastic optimization, reinforcement learning, and bandits.

Current focus

I work on adaptive algorithms for continual decision-making in real-world settings, including non-stationarity, distribution shift, delayed feedback, heavy-tailed noise, and bias.